Rename FastMCP to MCPServer (#1951)
This commit is contained in:
Marcelo Trylesinski
GitHub
parent
4a2d83a0cb
commit
65c614e48e
123 changed files with 713 additions and 693 deletions
2
.github/ISSUE_TEMPLATE/bug.yaml
vendored
2
.github/ISSUE_TEMPLATE/bug.yaml
vendored
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@ -39,7 +39,7 @@ body:
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demonstrating the bug.
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placeholder: |
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from mcp.server.fastmcp import FastMCP
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from mcp.server.mcpserver import MCPServer
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...
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render: Python
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184
README.md
184
README.md
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@ -45,7 +45,7 @@
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- [Sampling](#sampling)
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- [Logging and Notifications](#logging-and-notifications)
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- [Authentication](#authentication)
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- [FastMCP Properties](#fastmcp-properties)
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- [MCPServer Properties](#mcpserver-properties)
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- [Session Properties and Methods](#session-properties-and-methods)
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- [Request Context Properties](#request-context-properties)
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- [Running Your Server](#running-your-server)
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@ -134,18 +134,18 @@ uv run mcp
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Let's create a simple MCP server that exposes a calculator tool and some data:
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<!-- snippet-source examples/snippets/servers/fastmcp_quickstart.py -->
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<!-- snippet-source examples/snippets/servers/mcpserver_quickstart.py -->
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```python
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"""FastMCP quickstart example.
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"""MCPServer quickstart example.
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Run from the repository root:
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uv run examples/snippets/servers/fastmcp_quickstart.py
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uv run examples/snippets/servers/mcpserver_quickstart.py
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"""
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from mcp.server.fastmcp import FastMCP
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from mcp.server.mcpserver import MCPServer
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# Create an MCP server
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mcp = FastMCP("Demo")
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mcp = MCPServer("Demo")
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# Add an addition tool
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@ -180,13 +180,13 @@ if __name__ == "__main__":
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mcp.run(transport="streamable-http", json_response=True)
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```
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_Full example: [examples/snippets/servers/fastmcp_quickstart.py](https://github.com/modelcontextprotocol/python-sdk/blob/main/examples/snippets/servers/fastmcp_quickstart.py)_
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_Full example: [examples/snippets/servers/mcpserver_quickstart.py](https://github.com/modelcontextprotocol/python-sdk/blob/main/examples/snippets/servers/mcpserver_quickstart.py)_
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<!-- /snippet-source -->
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You can install this server in [Claude Code](https://docs.claude.com/en/docs/claude-code/mcp) and interact with it right away. First, run the server:
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```bash
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uv run --with mcp examples/snippets/servers/fastmcp_quickstart.py
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uv run --with mcp examples/snippets/servers/mcpserver_quickstart.py
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```
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Then add it to Claude Code:
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@ -216,7 +216,7 @@ The [Model Context Protocol (MCP)](https://modelcontextprotocol.io) lets you bui
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### Server
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The FastMCP server is your core interface to the MCP protocol. It handles connection management, protocol compliance, and message routing:
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The MCPServer server is your core interface to the MCP protocol. It handles connection management, protocol compliance, and message routing:
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<!-- snippet-source examples/snippets/servers/lifespan_example.py -->
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```python
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@ -226,7 +226,7 @@ from collections.abc import AsyncIterator
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from contextlib import asynccontextmanager
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from dataclasses import dataclass
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from mcp.server.fastmcp import Context, FastMCP
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from mcp.server.mcpserver import Context, MCPServer
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from mcp.server.session import ServerSession
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@ -256,7 +256,7 @@ class AppContext:
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@asynccontextmanager
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async def app_lifespan(server: FastMCP) -> AsyncIterator[AppContext]:
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async def app_lifespan(server: MCPServer) -> AsyncIterator[AppContext]:
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"""Manage application lifecycle with type-safe context."""
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# Initialize on startup
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db = await Database.connect()
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@ -268,7 +268,7 @@ async def app_lifespan(server: FastMCP) -> AsyncIterator[AppContext]:
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# Pass lifespan to server
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mcp = FastMCP("My App", lifespan=app_lifespan)
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mcp = MCPServer("My App", lifespan=app_lifespan)
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# Access type-safe lifespan context in tools
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@ -288,9 +288,9 @@ Resources are how you expose data to LLMs. They're similar to GET endpoints in a
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<!-- snippet-source examples/snippets/servers/basic_resource.py -->
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```python
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from mcp.server.fastmcp import FastMCP
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from mcp.server.mcpserver import MCPServer
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mcp = FastMCP(name="Resource Example")
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mcp = MCPServer(name="Resource Example")
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@mcp.resource("file://documents/{name}")
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@ -319,9 +319,9 @@ Tools let LLMs take actions through your server. Unlike resources, tools are exp
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<!-- snippet-source examples/snippets/servers/basic_tool.py -->
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```python
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from mcp.server.fastmcp import FastMCP
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from mcp.server.mcpserver import MCPServer
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mcp = FastMCP(name="Tool Example")
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mcp = MCPServer(name="Tool Example")
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@mcp.tool()
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@ -340,14 +340,14 @@ def get_weather(city: str, unit: str = "celsius") -> str:
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_Full example: [examples/snippets/servers/basic_tool.py](https://github.com/modelcontextprotocol/python-sdk/blob/main/examples/snippets/servers/basic_tool.py)_
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<!-- /snippet-source -->
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Tools can optionally receive a Context object by including a parameter with the `Context` type annotation. This context is automatically injected by the FastMCP framework and provides access to MCP capabilities:
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Tools can optionally receive a Context object by including a parameter with the `Context` type annotation. This context is automatically injected by the MCPServer framework and provides access to MCP capabilities:
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<!-- snippet-source examples/snippets/servers/tool_progress.py -->
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```python
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from mcp.server.fastmcp import Context, FastMCP
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from mcp.server.mcpserver import Context, MCPServer
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from mcp.server.session import ServerSession
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mcp = FastMCP(name="Progress Example")
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mcp = MCPServer(name="Progress Example")
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@mcp.tool()
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@ -395,7 +395,7 @@ validated data that clients can easily process.
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**Note:** For backward compatibility, unstructured results are also
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returned. Unstructured results are provided for backward compatibility
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with previous versions of the MCP specification, and are quirks-compatible
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with previous versions of FastMCP in the current version of the SDK.
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with previous versions of MCPServer in the current version of the SDK.
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**Note:** In cases where a tool function's return type annotation
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causes the tool to be classified as structured _and this is undesirable_,
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@ -414,10 +414,10 @@ from typing import Annotated
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from pydantic import BaseModel
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from mcp.server.fastmcp import FastMCP
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from mcp.server.mcpserver import MCPServer
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from mcp.types import CallToolResult, TextContent
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mcp = FastMCP("CallToolResult Example")
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mcp = MCPServer("CallToolResult Example")
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class ValidationModel(BaseModel):
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@ -465,9 +465,9 @@ from typing import TypedDict
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from pydantic import BaseModel, Field
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from mcp.server.fastmcp import FastMCP
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from mcp.server.mcpserver import MCPServer
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mcp = FastMCP("Structured Output Example")
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mcp = MCPServer("Structured Output Example")
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# Using Pydantic models for rich structured data
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@ -567,10 +567,10 @@ Prompts are reusable templates that help LLMs interact with your server effectiv
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<!-- snippet-source examples/snippets/servers/basic_prompt.py -->
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```python
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from mcp.server.fastmcp import FastMCP
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from mcp.server.fastmcp.prompts import base
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from mcp.server.mcpserver import MCPServer
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from mcp.server.mcpserver.prompts import base
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mcp = FastMCP(name="Prompt Example")
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mcp = MCPServer(name="Prompt Example")
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@mcp.prompt(title="Code Review")
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@ -595,7 +595,7 @@ _Full example: [examples/snippets/servers/basic_prompt.py](https://github.com/mo
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MCP servers can provide icons for UI display. Icons can be added to the server implementation, tools, resources, and prompts:
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```python
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from mcp.server.fastmcp import FastMCP, Icon
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from mcp.server.mcpserver import MCPServer, Icon
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# Create an icon from a file path or URL
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icon = Icon(
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@ -605,7 +605,7 @@ icon = Icon(
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)
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# Add icons to server
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mcp = FastMCP(
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mcp = MCPServer(
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"My Server",
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website_url="https://example.com",
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icons=[icon]
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@ -623,21 +623,21 @@ def my_resource():
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return "content"
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```
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_Full example: [examples/fastmcp/icons_demo.py](https://github.com/modelcontextprotocol/python-sdk/blob/main/examples/fastmcp/icons_demo.py)_
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_Full example: [examples/mcpserver/icons_demo.py](https://github.com/modelcontextprotocol/python-sdk/blob/main/examples/mcpserver/icons_demo.py)_
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### Images
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FastMCP provides an `Image` class that automatically handles image data:
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MCPServer provides an `Image` class that automatically handles image data:
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<!-- snippet-source examples/snippets/servers/images.py -->
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```python
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"""Example showing image handling with FastMCP."""
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"""Example showing image handling with MCPServer."""
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from PIL import Image as PILImage
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from mcp.server.fastmcp import FastMCP, Image
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from mcp.server.mcpserver import Image, MCPServer
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mcp = FastMCP("Image Example")
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mcp = MCPServer("Image Example")
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@mcp.tool()
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@ -660,9 +660,9 @@ The Context object is automatically injected into tool and resource functions th
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To use context in a tool or resource function, add a parameter with the `Context` type annotation:
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```python
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from mcp.server.fastmcp import Context, FastMCP
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from mcp.server.mcpserver import Context, MCPServer
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mcp = FastMCP(name="Context Example")
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mcp = MCPServer(name="Context Example")
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@mcp.tool()
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@ -678,7 +678,7 @@ The Context object provides the following capabilities:
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- `ctx.request_id` - Unique ID for the current request
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- `ctx.client_id` - Client ID if available
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- `ctx.fastmcp` - Access to the FastMCP server instance (see [FastMCP Properties](#fastmcp-properties))
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- `ctx.mcp_server` - Access to the MCPServer server instance (see [MCPServer Properties](#mcpserver-properties))
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- `ctx.session` - Access to the underlying session for advanced communication (see [Session Properties and Methods](#session-properties-and-methods))
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- `ctx.request_context` - Access to request-specific data and lifespan resources (see [Request Context Properties](#request-context-properties))
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- `await ctx.debug(message)` - Send debug log message
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@ -692,10 +692,10 @@ The Context object provides the following capabilities:
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<!-- snippet-source examples/snippets/servers/tool_progress.py -->
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```python
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from mcp.server.fastmcp import Context, FastMCP
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from mcp.server.mcpserver import Context, MCPServer
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from mcp.server.session import ServerSession
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mcp = FastMCP(name="Progress Example")
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mcp = MCPServer(name="Progress Example")
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@mcp.tool()
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@ -824,12 +824,12 @@ import uuid
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from pydantic import BaseModel, Field
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from mcp.server.fastmcp import Context, FastMCP
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from mcp.server.mcpserver import Context, MCPServer
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from mcp.server.session import ServerSession
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from mcp.shared.exceptions import UrlElicitationRequiredError
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from mcp.types import ElicitRequestURLParams
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mcp = FastMCP(name="Elicitation Example")
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mcp = MCPServer(name="Elicitation Example")
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class BookingPreferences(BaseModel):
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<!-- snippet-source examples/snippets/servers/sampling.py -->
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```python
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from mcp.server.fastmcp import Context, FastMCP
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from mcp.server.mcpserver import Context, MCPServer
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from mcp.server.session import ServerSession
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from mcp.types import SamplingMessage, TextContent
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mcp = FastMCP(name="Sampling Example")
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mcp = MCPServer(name="Sampling Example")
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@mcp.tool()
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@ -968,10 +968,10 @@ Tools can send logs and notifications through the context:
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<!-- snippet-source examples/snippets/servers/notifications.py -->
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```python
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from mcp.server.fastmcp import Context, FastMCP
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from mcp.server.mcpserver import Context, MCPServer
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from mcp.server.session import ServerSession
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mcp = FastMCP(name="Notifications Example")
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mcp = MCPServer(name="Notifications Example")
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@mcp.tool()
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@ -1010,7 +1010,7 @@ from pydantic import AnyHttpUrl
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from mcp.server.auth.provider import AccessToken, TokenVerifier
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from mcp.server.auth.settings import AuthSettings
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from mcp.server.fastmcp import FastMCP
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from mcp.server.mcpserver import MCPServer
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class SimpleTokenVerifier(TokenVerifier):
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@ -1020,8 +1020,8 @@ class SimpleTokenVerifier(TokenVerifier):
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pass # This is where you would implement actual token validation
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# Create FastMCP instance as a Resource Server
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mcp = FastMCP(
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# Create MCPServer instance as a Resource Server
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mcp = MCPServer(
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"Weather Service",
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# Token verifier for authentication
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token_verifier=SimpleTokenVerifier(),
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@ -1062,15 +1062,15 @@ For a complete example with separate Authorization Server and Resource Server im
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See [TokenVerifier](src/mcp/server/auth/provider.py) for more details on implementing token validation.
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### FastMCP Properties
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### MCPServer Properties
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The FastMCP server instance accessible via `ctx.fastmcp` provides access to server configuration and metadata:
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The MCPServer server instance accessible via `ctx.mcp_server` provides access to server configuration and metadata:
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- `ctx.fastmcp.name` - The server's name as defined during initialization
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- `ctx.fastmcp.instructions` - Server instructions/description provided to clients
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- `ctx.fastmcp.website_url` - Optional website URL for the server
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- `ctx.fastmcp.icons` - Optional list of icons for UI display
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- `ctx.fastmcp.settings` - Complete server configuration object containing:
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- `ctx.mcp_server.name` - The server's name as defined during initialization
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- `ctx.mcp_server.instructions` - Server instructions/description provided to clients
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- `ctx.mcp_server.website_url` - Optional website URL for the server
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- `ctx.mcp_server.icons` - Optional list of icons for UI display
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- `ctx.mcp_server.settings` - Complete server configuration object containing:
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- `debug` - Debug mode flag
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- `log_level` - Current logging level
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- `host` and `port` - Server network configuration
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@ -1083,12 +1083,12 @@ The FastMCP server instance accessible via `ctx.fastmcp` provides access to serv
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def server_info(ctx: Context) -> dict:
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"""Get information about the current server."""
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return {
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"name": ctx.fastmcp.name,
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"instructions": ctx.fastmcp.instructions,
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"debug_mode": ctx.fastmcp.settings.debug,
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"log_level": ctx.fastmcp.settings.log_level,
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"host": ctx.fastmcp.settings.host,
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"port": ctx.fastmcp.settings.port,
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"name": ctx.mcp_server.name,
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"instructions": ctx.mcp_server.instructions,
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"debug_mode": ctx.mcp_server.settings.debug,
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"log_level": ctx.mcp_server.settings.log_level,
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"host": ctx.mcp_server.settings.host,
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"port": ctx.mcp_server.settings.port,
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}
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```
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@ -1203,9 +1203,9 @@ cd to the `examples/snippets` directory and run:
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python servers/direct_execution.py
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"""
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from mcp.server.fastmcp import FastMCP
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from mcp.server.mcpserver import MCPServer
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mcp = FastMCP("My App")
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mcp = MCPServer("My App")
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@mcp.tool()
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@ -1234,7 +1234,7 @@ python servers/direct_execution.py
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uv run mcp run servers/direct_execution.py
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```
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Note that `uv run mcp run` or `uv run mcp dev` only supports server using FastMCP and not the low-level server variant.
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Note that `uv run mcp run` or `uv run mcp dev` only supports server using MCPServer and not the low-level server variant.
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### Streamable HTTP Transport
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@ -1246,9 +1246,9 @@ Note that `uv run mcp run` or `uv run mcp dev` only supports server using FastMC
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uv run examples/snippets/servers/streamable_config.py
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"""
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from mcp.server.fastmcp import FastMCP
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from mcp.server.mcpserver import MCPServer
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mcp = FastMCP("StatelessServer")
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mcp = MCPServer("StatelessServer")
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# Add a simple tool to demonstrate the server
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@ -1275,7 +1275,7 @@ if __name__ == "__main__":
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_Full example: [examples/snippets/servers/streamable_config.py](https://github.com/modelcontextprotocol/python-sdk/blob/main/examples/snippets/servers/streamable_config.py)_
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<!-- /snippet-source -->
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You can mount multiple FastMCP servers in a Starlette application:
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You can mount multiple MCPServer servers in a Starlette application:
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<!-- snippet-source examples/snippets/servers/streamable_starlette_mount.py -->
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```python
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@ -1288,10 +1288,10 @@ import contextlib
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from starlette.applications import Starlette
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from starlette.routing import Mount
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from mcp.server.fastmcp import FastMCP
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from mcp.server.mcpserver import MCPServer
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# Create the Echo server
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echo_mcp = FastMCP(name="EchoServer")
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echo_mcp = MCPServer(name="EchoServer")
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||||
@echo_mcp.tool()
|
||||
|
|
@ -1301,7 +1301,7 @@ def echo(message: str) -> str:
|
|||
|
||||
|
||||
# Create the Math server
|
||||
math_mcp = FastMCP(name="MathServer")
|
||||
math_mcp = MCPServer(name="MathServer")
|
||||
|
||||
|
||||
@math_mcp.tool()
|
||||
|
|
@ -1400,10 +1400,10 @@ import contextlib
|
|||
from starlette.applications import Starlette
|
||||
from starlette.routing import Mount
|
||||
|
||||
from mcp.server.fastmcp import FastMCP
|
||||
from mcp.server.mcpserver import MCPServer
|
||||
|
||||
# Create MCP server
|
||||
mcp = FastMCP("My App")
|
||||
mcp = MCPServer("My App")
|
||||
|
||||
|
||||
@mcp.tool()
|
||||
|
|
@ -1447,10 +1447,10 @@ import contextlib
|
|||
from starlette.applications import Starlette
|
||||
from starlette.routing import Host
|
||||
|
||||
from mcp.server.fastmcp import FastMCP
|
||||
from mcp.server.mcpserver import MCPServer
|
||||
|
||||
# Create MCP server
|
||||
mcp = FastMCP("MCP Host App")
|
||||
mcp = MCPServer("MCP Host App")
|
||||
|
||||
|
||||
@mcp.tool()
|
||||
|
|
@ -1494,11 +1494,11 @@ import contextlib
|
|||
from starlette.applications import Starlette
|
||||
from starlette.routing import Mount
|
||||
|
||||
from mcp.server.fastmcp import FastMCP
|
||||
from mcp.server.mcpserver import MCPServer
|
||||
|
||||
# Create multiple MCP servers
|
||||
api_mcp = FastMCP("API Server")
|
||||
chat_mcp = FastMCP("Chat Server")
|
||||
api_mcp = MCPServer("API Server")
|
||||
chat_mcp = MCPServer("Chat Server")
|
||||
|
||||
|
||||
@api_mcp.tool()
|
||||
|
|
@ -1540,7 +1540,7 @@ _Full example: [examples/snippets/servers/streamable_http_multiple_servers.py](h
|
|||
|
||||
<!-- snippet-source examples/snippets/servers/streamable_http_path_config.py -->
|
||||
```python
|
||||
"""Example showing path configuration when mounting FastMCP.
|
||||
"""Example showing path configuration when mounting MCPServer.
|
||||
|
||||
Run from the repository root:
|
||||
uvicorn examples.snippets.servers.streamable_http_path_config:app --reload
|
||||
|
|
@ -1549,10 +1549,10 @@ Run from the repository root:
|
|||
from starlette.applications import Starlette
|
||||
from starlette.routing import Mount
|
||||
|
||||
from mcp.server.fastmcp import FastMCP
|
||||
from mcp.server.mcpserver import MCPServer
|
||||
|
||||
# Create a simple FastMCP server
|
||||
mcp_at_root = FastMCP("My Server")
|
||||
# Create a simple MCPServer server
|
||||
mcp_at_root = MCPServer("My Server")
|
||||
|
||||
|
||||
@mcp_at_root.tool()
|
||||
|
|
@ -1585,10 +1585,10 @@ You can mount the SSE server to an existing ASGI server using the `sse_app` meth
|
|||
```python
|
||||
from starlette.applications import Starlette
|
||||
from starlette.routing import Mount, Host
|
||||
from mcp.server.fastmcp import FastMCP
|
||||
from mcp.server.mcpserver import MCPServer
|
||||
|
||||
|
||||
mcp = FastMCP("My App")
|
||||
mcp = MCPServer("My App")
|
||||
|
||||
# Mount the SSE server to the existing ASGI server
|
||||
app = Starlette(
|
||||
|
|
@ -1606,12 +1606,12 @@ You can also mount multiple MCP servers at different sub-paths. The SSE transpor
|
|||
```python
|
||||
from starlette.applications import Starlette
|
||||
from starlette.routing import Mount
|
||||
from mcp.server.fastmcp import FastMCP
|
||||
from mcp.server.mcpserver import MCPServer
|
||||
|
||||
# Create multiple MCP servers
|
||||
github_mcp = FastMCP("GitHub API")
|
||||
browser_mcp = FastMCP("Browser")
|
||||
search_mcp = FastMCP("Search")
|
||||
github_mcp = MCPServer("GitHub API")
|
||||
browser_mcp = MCPServer("Browser")
|
||||
search_mcp = MCPServer("Search")
|
||||
|
||||
# Mount each server at its own sub-path
|
||||
# The SSE transport automatically uses ASGI's root_path to construct
|
||||
|
|
@ -2126,7 +2126,7 @@ from mcp.shared.context import RequestContext
|
|||
# Create server parameters for stdio connection
|
||||
server_params = StdioServerParameters(
|
||||
command="uv", # Using uv to run the server
|
||||
args=["run", "server", "fastmcp_quickstart", "stdio"], # We're already in snippets dir
|
||||
args=["run", "server", "mcpserver_quickstart", "stdio"], # We're already in snippets dir
|
||||
env={"UV_INDEX": os.environ.get("UV_INDEX", "")},
|
||||
)
|
||||
|
||||
|
|
@ -2157,7 +2157,7 @@ async def run():
|
|||
prompts = await session.list_prompts()
|
||||
print(f"Available prompts: {[p.name for p in prompts.prompts]}")
|
||||
|
||||
# Get a prompt (greet_user prompt from fastmcp_quickstart)
|
||||
# Get a prompt (greet_user prompt from mcpserver_quickstart)
|
||||
if prompts.prompts:
|
||||
prompt = await session.get_prompt("greet_user", arguments={"name": "Alice", "style": "friendly"})
|
||||
print(f"Prompt result: {prompt.messages[0].content}")
|
||||
|
|
@ -2170,13 +2170,13 @@ async def run():
|
|||
tools = await session.list_tools()
|
||||
print(f"Available tools: {[t.name for t in tools.tools]}")
|
||||
|
||||
# Read a resource (greeting resource from fastmcp_quickstart)
|
||||
# Read a resource (greeting resource from mcpserver_quickstart)
|
||||
resource_content = await session.read_resource("greeting://World")
|
||||
content_block = resource_content.contents[0]
|
||||
if isinstance(content_block, types.TextContent):
|
||||
print(f"Resource content: {content_block.text}")
|
||||
|
||||
# Call a tool (add tool from fastmcp_quickstart)
|
||||
# Call a tool (add tool from mcpserver_quickstart)
|
||||
result = await session.call_tool("add", arguments={"a": 5, "b": 3})
|
||||
result_unstructured = result.content[0]
|
||||
if isinstance(result_unstructured, types.TextContent):
|
||||
|
|
@ -2254,7 +2254,7 @@ from mcp.shared.metadata_utils import get_display_name
|
|||
# Create server parameters for stdio connection
|
||||
server_params = StdioServerParameters(
|
||||
command="uv", # Using uv to run the server
|
||||
args=["run", "server", "fastmcp_quickstart", "stdio"],
|
||||
args=["run", "server", "mcpserver_quickstart", "stdio"],
|
||||
env={"UV_INDEX": os.environ.get("UV_INDEX", "")},
|
||||
)
|
||||
|
||||
|
|
|
|||
|
|
@ -15,9 +15,9 @@ If you want to read more about the specification, please visit the [MCP document
|
|||
Here's a simple MCP server that exposes a tool, resource, and prompt:
|
||||
|
||||
```python title="server.py"
|
||||
from mcp.server.fastmcp import FastMCP
|
||||
from mcp.server.mcpserver import MCPServer
|
||||
|
||||
mcp = FastMCP("Test Server", json_response=True)
|
||||
mcp = MCPServer("Test Server", json_response=True)
|
||||
|
||||
|
||||
@mcp.tool()
|
||||
|
|
|
|||
|
|
@ -21,7 +21,7 @@ The following dependencies are automatically installed:
|
|||
- [`starlette`](https://pypi.org/project/starlette/): Web framework used to build the HTTP transport endpoints.
|
||||
- [`python-multipart`](https://pypi.org/project/python-multipart/): Handle HTTP body parsing.
|
||||
- [`sse-starlette`](https://pypi.org/project/sse-starlette/): Server-Sent Events for Starlette, used to build the SSE transport endpoint.
|
||||
- [`pydantic-settings`](https://pypi.org/project/pydantic-settings/): Settings management used in FastMCP.
|
||||
- [`pydantic-settings`](https://pypi.org/project/pydantic-settings/): Settings management used in MCPServer.
|
||||
- [`uvicorn`](https://pypi.org/project/uvicorn/): ASGI server used to run the HTTP transport endpoints.
|
||||
- [`jsonschema`](https://pypi.org/project/jsonschema/): JSON schema validation.
|
||||
- [`pywin32`](https://pypi.org/project/pywin32/): Windows specific dependencies for the CLI tools.
|
||||
|
|
|
|||
|
|
@ -121,15 +121,35 @@ result = await session.list_resources(params=PaginatedRequestParams(cursor="next
|
|||
result = await session.list_tools(params=PaginatedRequestParams(cursor="next_page_token"))
|
||||
```
|
||||
|
||||
### `mount_path` parameter removed from FastMCP
|
||||
### `FastMCP` renamed to `MCPServer`
|
||||
|
||||
The `mount_path` parameter has been removed from `FastMCP.__init__()`, `FastMCP.run()`, `FastMCP.run_sse_async()`, and `FastMCP.sse_app()`. It was also removed from the `Settings` class.
|
||||
The `FastMCP` class has been renamed to `MCPServer` to better reflect its role as the main server class in the SDK. This is a simple rename with no functional changes to the class itself.
|
||||
|
||||
**Before (v1):**
|
||||
|
||||
```python
|
||||
from mcp.server.fastmcp import FastMCP
|
||||
|
||||
mcp = FastMCP("Demo")
|
||||
```
|
||||
|
||||
**After (v2):**
|
||||
|
||||
```python
|
||||
from mcp.server.mcpserver import MCPServer
|
||||
|
||||
mcp = MCPServer("Demo")
|
||||
```
|
||||
|
||||
### `mount_path` parameter removed from MCPServer
|
||||
|
||||
The `mount_path` parameter has been removed from `MCPServer.__init__()`, `MCPServer.run()`, `MCPServer.run_sse_async()`, and `MCPServer.sse_app()`. It was also removed from the `Settings` class.
|
||||
|
||||
This parameter was redundant because the SSE transport already handles sub-path mounting via ASGI's standard `root_path` mechanism. When using Starlette's `Mount("/path", app=mcp.sse_app())`, Starlette automatically sets `root_path` in the ASGI scope, and the `SseServerTransport` uses this to construct the correct message endpoint path.
|
||||
|
||||
### Transport-specific parameters moved from FastMCP constructor to run()/app methods
|
||||
### Transport-specific parameters moved from MCPServer constructor to run()/app methods
|
||||
|
||||
Transport-specific parameters have been moved from the `FastMCP` constructor to the `run()`, `sse_app()`, and `streamable_http_app()` methods. This provides better separation of concerns - the constructor now only handles server identity and authentication, while transport configuration is passed when starting the server.
|
||||
Transport-specific parameters have been moved from the `MCPServer` constructor to the `run()`, `sse_app()`, and `streamable_http_app()` methods. This provides better separation of concerns - the constructor now only handles server identity and authentication, while transport configuration is passed when starting the server.
|
||||
|
||||
**Parameters moved:**
|
||||
|
||||
|
|
@ -157,28 +177,32 @@ mcp.run(transport="sse")
|
|||
**After (v2):**
|
||||
|
||||
```python
|
||||
from mcp.server.fastmcp import FastMCP
|
||||
from mcp.server.mcpserver import MCPServer
|
||||
|
||||
# Transport params passed to run()
|
||||
mcp = FastMCP("Demo")
|
||||
mcp = MCPServer("Demo")
|
||||
mcp.run(transport="streamable-http", json_response=True, stateless_http=True)
|
||||
|
||||
# Or for SSE
|
||||
mcp = FastMCP("Server")
|
||||
mcp = MCPServer("Server")
|
||||
mcp.run(transport="sse", host="0.0.0.0", port=9000, sse_path="/events")
|
||||
```
|
||||
|
||||
**For mounted apps:**
|
||||
|
||||
When mounting FastMCP in a Starlette app, pass transport params to the app methods:
|
||||
When mounting in a Starlette app, pass transport params to the app methods:
|
||||
|
||||
```python
|
||||
# Before (v1)
|
||||
from mcp.server.fastmcp import FastMCP
|
||||
|
||||
mcp = FastMCP("App", json_response=True)
|
||||
app = Starlette(routes=[Mount("/", app=mcp.streamable_http_app())])
|
||||
|
||||
# After (v2)
|
||||
mcp = FastMCP("App")
|
||||
from mcp.server.mcpserver import MCPServer
|
||||
|
||||
mcp = MCPServer("App")
|
||||
app = Starlette(routes=[Mount("/", app=mcp.streamable_http_app(json_response=True))])
|
||||
```
|
||||
|
||||
|
|
@ -354,7 +378,7 @@ params = CallToolRequestParams(
|
|||
|
||||
### `streamable_http_app()` available on lowlevel Server
|
||||
|
||||
The `streamable_http_app()` method is now available directly on the lowlevel `Server` class, not just `FastMCP`. This allows using the streamable HTTP transport without the FastMCP wrapper.
|
||||
The `streamable_http_app()` method is now available directly on the lowlevel `Server` class, not just `MCPServer`. This allows using the streamable HTTP transport without the MCPServer wrapper.
|
||||
|
||||
```python
|
||||
from mcp.server.lowlevel.server import Server
|
||||
|
|
|
|||
|
|
@ -8,9 +8,9 @@ This makes it easy to write tests without network overhead.
|
|||
Let's assume you have a simple server with a single tool:
|
||||
|
||||
```python title="server.py"
|
||||
from mcp.server import FastMCP
|
||||
from mcp.server import MCPServer
|
||||
|
||||
app = FastMCP("Calculator")
|
||||
app = MCPServer("Calculator")
|
||||
|
||||
@app.tool()
|
||||
def add(a: int, b: int) -> int:
|
||||
|
|
|
|||
29
examples/mcpserver/complex_inputs.py
Normal file
29
examples/mcpserver/complex_inputs.py
Normal file
|
|
@ -0,0 +1,29 @@
|
|||
"""MCPServer Complex inputs Example
|
||||
|
||||
Demonstrates validation via pydantic with complex models.
|
||||
"""
|
||||
|
||||
from typing import Annotated
|
||||
|
||||
from pydantic import BaseModel, Field
|
||||
|
||||
from mcp.server.mcpserver import MCPServer
|
||||
|
||||
mcp = MCPServer("Shrimp Tank")
|
||||
|
||||
|
||||
class ShrimpTank(BaseModel):
|
||||
class Shrimp(BaseModel):
|
||||
name: Annotated[str, Field(max_length=10)]
|
||||
|
||||
shrimp: list[Shrimp]
|
||||
|
||||
|
||||
@mcp.tool()
|
||||
def name_shrimp(
|
||||
tank: ShrimpTank,
|
||||
# You can use pydantic Field in function signatures for validation.
|
||||
extra_names: Annotated[list[str], Field(max_length=10)],
|
||||
) -> list[str]:
|
||||
"""List all shrimp names in the tank"""
|
||||
return [shrimp.name for shrimp in tank.shrimp] + extra_names
|
||||
24
examples/mcpserver/desktop.py
Normal file
24
examples/mcpserver/desktop.py
Normal file
|
|
@ -0,0 +1,24 @@
|
|||
"""MCPServer Desktop Example
|
||||
|
||||
A simple example that exposes the desktop directory as a resource.
|
||||
"""
|
||||
|
||||
from pathlib import Path
|
||||
|
||||
from mcp.server.mcpserver import MCPServer
|
||||
|
||||
# Create server
|
||||
mcp = MCPServer("Demo")
|
||||
|
||||
|
||||
@mcp.resource("dir://desktop")
|
||||
def desktop() -> list[str]:
|
||||
"""List the files in the user's desktop"""
|
||||
desktop = Path.home() / "Desktop"
|
||||
return [str(f) for f in desktop.iterdir()]
|
||||
|
||||
|
||||
@mcp.tool()
|
||||
def sum(a: int, b: int) -> int:
|
||||
"""Add two numbers"""
|
||||
return a + b
|
||||
22
examples/mcpserver/direct_call_tool_result_return.py
Normal file
22
examples/mcpserver/direct_call_tool_result_return.py
Normal file
|
|
@ -0,0 +1,22 @@
|
|||
"""MCPServer Echo Server with direct CallToolResult return"""
|
||||
|
||||
from typing import Annotated
|
||||
|
||||
from pydantic import BaseModel
|
||||
|
||||
from mcp.server.mcpserver import MCPServer
|
||||
from mcp.types import CallToolResult, TextContent
|
||||
|
||||
mcp = MCPServer("Echo Server")
|
||||
|
||||
|
||||
class EchoResponse(BaseModel):
|
||||
text: str
|
||||
|
||||
|
||||
@mcp.tool()
|
||||
def echo(text: str) -> Annotated[CallToolResult, EchoResponse]:
|
||||
"""Echo the input text with structure and metadata"""
|
||||
return CallToolResult(
|
||||
content=[TextContent(type="text", text=text)], structured_content={"text": text}, _meta={"some": "metadata"}
|
||||
)
|
||||
28
examples/mcpserver/echo.py
Normal file
28
examples/mcpserver/echo.py
Normal file
|
|
@ -0,0 +1,28 @@
|
|||
"""MCPServer Echo Server"""
|
||||
|
||||
from mcp.server.mcpserver import MCPServer
|
||||
|
||||
# Create server
|
||||
mcp = MCPServer("Echo Server")
|
||||
|
||||
|
||||
@mcp.tool()
|
||||
def echo_tool(text: str) -> str:
|
||||
"""Echo the input text"""
|
||||
return text
|
||||
|
||||
|
||||
@mcp.resource("echo://static")
|
||||
def echo_resource() -> str:
|
||||
return "Echo!"
|
||||
|
||||
|
||||
@mcp.resource("echo://{text}")
|
||||
def echo_template(text: str) -> str:
|
||||
"""Echo the input text"""
|
||||
return f"Echo: {text}"
|
||||
|
||||
|
||||
@mcp.prompt("echo")
|
||||
def echo_prompt(text: str) -> str:
|
||||
return text
|
||||
56
examples/mcpserver/icons_demo.py
Normal file
56
examples/mcpserver/icons_demo.py
Normal file
|
|
@ -0,0 +1,56 @@
|
|||
"""MCPServer Icons Demo Server
|
||||
|
||||
Demonstrates using icons with tools, resources, prompts, and implementation.
|
||||
"""
|
||||
|
||||
import base64
|
||||
from pathlib import Path
|
||||
|
||||
from mcp.server.mcpserver import Icon, MCPServer
|
||||
|
||||
# Load the icon file and convert to data URI
|
||||
icon_path = Path(__file__).parent / "mcp.png"
|
||||
icon_data = base64.standard_b64encode(icon_path.read_bytes()).decode()
|
||||
icon_data_uri = f"data:image/png;base64,{icon_data}"
|
||||
|
||||
icon_data = Icon(src=icon_data_uri, mime_type="image/png", sizes=["64x64"])
|
||||
|
||||
# Create server with icons in implementation
|
||||
mcp = MCPServer(
|
||||
"Icons Demo Server", website_url="https://github.com/modelcontextprotocol/python-sdk", icons=[icon_data]
|
||||
)
|
||||
|
||||
|
||||
@mcp.tool(icons=[icon_data])
|
||||
def demo_tool(message: str) -> str:
|
||||
"""A demo tool with an icon."""
|
||||
return message
|
||||
|
||||
|
||||
@mcp.resource("demo://readme", icons=[icon_data])
|
||||
def readme_resource() -> str:
|
||||
"""A demo resource with an icon"""
|
||||
return "This resource has an icon"
|
||||
|
||||
|
||||
@mcp.prompt("prompt_with_icon", icons=[icon_data])
|
||||
def prompt_with_icon(text: str) -> str:
|
||||
"""A demo prompt with an icon"""
|
||||
return text
|
||||
|
||||
|
||||
@mcp.tool(
|
||||
icons=[
|
||||
Icon(src=icon_data_uri, mime_type="image/png", sizes=["16x16"]),
|
||||
Icon(src=icon_data_uri, mime_type="image/png", sizes=["32x32"]),
|
||||
Icon(src=icon_data_uri, mime_type="image/png", sizes=["64x64"]),
|
||||
]
|
||||
)
|
||||
def multi_icon_tool(action: str) -> str:
|
||||
"""A tool demonstrating multiple icons."""
|
||||
return "multi_icon_tool"
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
# Run the server
|
||||
mcp.run()
|
||||
31
examples/mcpserver/logging_and_progress.py
Normal file
31
examples/mcpserver/logging_and_progress.py
Normal file
|
|
@ -0,0 +1,31 @@
|
|||
"""MCPServer Echo Server that sends log messages and progress updates to the client"""
|
||||
|
||||
import asyncio
|
||||
|
||||
from mcp.server.mcpserver import Context, MCPServer
|
||||
|
||||
# Create server
|
||||
mcp = MCPServer("Echo Server with logging and progress updates")
|
||||
|
||||
|
||||
@mcp.tool()
|
||||
async def echo(text: str, ctx: Context) -> str:
|
||||
"""Echo the input text sending log messages and progress updates during processing."""
|
||||
await ctx.report_progress(progress=0, total=100)
|
||||
await ctx.info("Starting to process echo for input: " + text)
|
||||
|
||||
await asyncio.sleep(2)
|
||||
|
||||
await ctx.info("Halfway through processing echo for input: " + text)
|
||||
await ctx.report_progress(progress=50, total=100)
|
||||
|
||||
await asyncio.sleep(2)
|
||||
|
||||
await ctx.info("Finished processing echo for input: " + text)
|
||||
await ctx.report_progress(progress=100, total=100)
|
||||
|
||||
# Progress notifications are process asynchronously by the client.
|
||||
# A small delay here helps ensure the last notification is processed by the client.
|
||||
await asyncio.sleep(0.1)
|
||||
|
||||
return text
|
||||
BIN
examples/mcpserver/mcp.png
Normal file
BIN
examples/mcpserver/mcp.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 2.5 KiB |
324
examples/mcpserver/memory.py
Normal file
324
examples/mcpserver/memory.py
Normal file
|
|
@ -0,0 +1,324 @@
|
|||
# /// script
|
||||
# dependencies = ["pydantic-ai-slim[openai]", "asyncpg", "numpy", "pgvector"]
|
||||
# ///
|
||||
|
||||
# uv pip install 'pydantic-ai-slim[openai]' asyncpg numpy pgvector
|
||||
|
||||
"""Recursive memory system inspired by the human brain's clustering of memories.
|
||||
Uses OpenAI's 'text-embedding-3-small' model and pgvector for efficient
|
||||
similarity search.
|
||||
"""
|
||||
|
||||
import asyncio
|
||||
import math
|
||||
import os
|
||||
from dataclasses import dataclass
|
||||
from datetime import datetime, timezone
|
||||
from pathlib import Path
|
||||
from typing import Annotated, Self, TypeVar
|
||||
|
||||
import asyncpg
|
||||
import numpy as np
|
||||
from openai import AsyncOpenAI
|
||||
from pgvector.asyncpg import register_vector # Import register_vector
|
||||
from pydantic import BaseModel, Field
|
||||
from pydantic_ai import Agent
|
||||
|
||||
from mcp.server.mcpserver import MCPServer
|
||||
|
||||
MAX_DEPTH = 5
|
||||
SIMILARITY_THRESHOLD = 0.7
|
||||
DECAY_FACTOR = 0.99
|
||||
REINFORCEMENT_FACTOR = 1.1
|
||||
|
||||
DEFAULT_LLM_MODEL = "openai:gpt-4o"
|
||||
DEFAULT_EMBEDDING_MODEL = "text-embedding-3-small"
|
||||
|
||||
T = TypeVar("T")
|
||||
|
||||
mcp = MCPServer("memory")
|
||||
|
||||
DB_DSN = "postgresql://postgres:postgres@localhost:54320/memory_db"
|
||||
# reset memory with rm ~/.mcp/{USER}/memory/*
|
||||
PROFILE_DIR = (Path.home() / ".mcp" / os.environ.get("USER", "anon") / "memory").resolve()
|
||||
PROFILE_DIR.mkdir(parents=True, exist_ok=True)
|
||||
|
||||
|
||||
def cosine_similarity(a: list[float], b: list[float]) -> float:
|
||||
a_array = np.array(a, dtype=np.float64)
|
||||
b_array = np.array(b, dtype=np.float64)
|
||||
return np.dot(a_array, b_array) / (np.linalg.norm(a_array) * np.linalg.norm(b_array))
|
||||
|
||||
|
||||
async def do_ai(
|
||||
user_prompt: str,
|
||||
system_prompt: str,
|
||||
result_type: type[T] | Annotated,
|
||||
deps=None,
|
||||
) -> T:
|
||||
agent = Agent(
|
||||
DEFAULT_LLM_MODEL,
|
||||
system_prompt=system_prompt,
|
||||
result_type=result_type,
|
||||
)
|
||||
result = await agent.run(user_prompt, deps=deps)
|
||||
return result.data
|
||||
|
||||
|
||||
@dataclass
|
||||
class Deps:
|
||||
openai: AsyncOpenAI
|
||||
pool: asyncpg.Pool
|
||||
|
||||
|
||||
async def get_db_pool() -> asyncpg.Pool:
|
||||
async def init(conn):
|
||||
await conn.execute("CREATE EXTENSION IF NOT EXISTS vector;")
|
||||
await register_vector(conn)
|
||||
|
||||
pool = await asyncpg.create_pool(DB_DSN, init=init)
|
||||
return pool
|
||||
|
||||
|
||||
class MemoryNode(BaseModel):
|
||||
id: int | None = None
|
||||
content: str
|
||||
summary: str = ""
|
||||
importance: float = 1.0
|
||||
access_count: int = 0
|
||||
timestamp: float = Field(default_factory=lambda: datetime.now(timezone.utc).timestamp())
|
||||
embedding: list[float]
|
||||
|
||||
@classmethod
|
||||
async def from_content(cls, content: str, deps: Deps):
|
||||
embedding = await get_embedding(content, deps)
|
||||
return cls(content=content, embedding=embedding)
|
||||
|
||||
async def save(self, deps: Deps):
|
||||
async with deps.pool.acquire() as conn:
|
||||
if self.id is None:
|
||||
result = await conn.fetchrow(
|
||||
"""
|
||||
INSERT INTO memories (content, summary, importance, access_count,
|
||||
timestamp, embedding)
|
||||
VALUES ($1, $2, $3, $4, $5, $6)
|
||||
RETURNING id
|
||||
""",
|
||||
self.content,
|
||||
self.summary,
|
||||
self.importance,
|
||||
self.access_count,
|
||||
self.timestamp,
|
||||
self.embedding,
|
||||
)
|
||||
self.id = result["id"]
|
||||
else:
|
||||
await conn.execute(
|
||||
"""
|
||||
UPDATE memories
|
||||
SET content = $1, summary = $2, importance = $3,
|
||||
access_count = $4, timestamp = $5, embedding = $6
|
||||
WHERE id = $7
|
||||
""",
|
||||
self.content,
|
||||
self.summary,
|
||||
self.importance,
|
||||
self.access_count,
|
||||
self.timestamp,
|
||||
self.embedding,
|
||||
self.id,
|
||||
)
|
||||
|
||||
async def merge_with(self, other: Self, deps: Deps):
|
||||
self.content = await do_ai(
|
||||
f"{self.content}\n\n{other.content}",
|
||||
"Combine the following two texts into a single, coherent text.",
|
||||
str,
|
||||
deps,
|
||||
)
|
||||
self.importance += other.importance
|
||||
self.access_count += other.access_count
|
||||
self.embedding = [(a + b) / 2 for a, b in zip(self.embedding, other.embedding)]
|
||||
self.summary = await do_ai(self.content, "Summarize the following text concisely.", str, deps)
|
||||
await self.save(deps)
|
||||
# Delete the merged node from the database
|
||||
if other.id is not None:
|
||||
await delete_memory(other.id, deps)
|
||||
|
||||
def get_effective_importance(self):
|
||||
return self.importance * (1 + math.log(self.access_count + 1))
|
||||
|
||||
|
||||
async def get_embedding(text: str, deps: Deps) -> list[float]:
|
||||
embedding_response = await deps.openai.embeddings.create(
|
||||
input=text,
|
||||
model=DEFAULT_EMBEDDING_MODEL,
|
||||
)
|
||||
return embedding_response.data[0].embedding
|
||||
|
||||
|
||||
async def delete_memory(memory_id: int, deps: Deps):
|
||||
async with deps.pool.acquire() as conn:
|
||||
await conn.execute("DELETE FROM memories WHERE id = $1", memory_id)
|
||||
|
||||
|
||||
async def add_memory(content: str, deps: Deps):
|
||||
new_memory = await MemoryNode.from_content(content, deps)
|
||||
await new_memory.save(deps)
|
||||
|
||||
similar_memories = await find_similar_memories(new_memory.embedding, deps)
|
||||
for memory in similar_memories:
|
||||
if memory.id != new_memory.id:
|
||||
await new_memory.merge_with(memory, deps)
|
||||
|
||||
await update_importance(new_memory.embedding, deps)
|
||||
|
||||
await prune_memories(deps)
|
||||
|
||||
return f"Remembered: {content}"
|
||||
|
||||
|
||||
async def find_similar_memories(embedding: list[float], deps: Deps) -> list[MemoryNode]:
|
||||
async with deps.pool.acquire() as conn:
|
||||
rows = await conn.fetch(
|
||||
"""
|
||||
SELECT id, content, summary, importance, access_count, timestamp, embedding
|
||||
FROM memories
|
||||
ORDER BY embedding <-> $1
|
||||
LIMIT 5
|
||||
""",
|
||||
embedding,
|
||||
)
|
||||
memories = [
|
||||
MemoryNode(
|
||||
id=row["id"],
|
||||
content=row["content"],
|
||||
summary=row["summary"],
|
||||
importance=row["importance"],
|
||||
access_count=row["access_count"],
|
||||
timestamp=row["timestamp"],
|
||||
embedding=row["embedding"],
|
||||
)
|
||||
for row in rows
|
||||
]
|
||||
return memories
|
||||
|
||||
|
||||
async def update_importance(user_embedding: list[float], deps: Deps):
|
||||
async with deps.pool.acquire() as conn:
|
||||
rows = await conn.fetch("SELECT id, importance, access_count, embedding FROM memories")
|
||||
for row in rows:
|
||||
memory_embedding = row["embedding"]
|
||||
similarity = cosine_similarity(user_embedding, memory_embedding)
|
||||
if similarity > SIMILARITY_THRESHOLD:
|
||||
new_importance = row["importance"] * REINFORCEMENT_FACTOR
|
||||
new_access_count = row["access_count"] + 1
|
||||
else:
|
||||
new_importance = row["importance"] * DECAY_FACTOR
|
||||
new_access_count = row["access_count"]
|
||||
await conn.execute(
|
||||
"""
|
||||
UPDATE memories
|
||||
SET importance = $1, access_count = $2
|
||||
WHERE id = $3
|
||||
""",
|
||||
new_importance,
|
||||
new_access_count,
|
||||
row["id"],
|
||||
)
|
||||
|
||||
|
||||
async def prune_memories(deps: Deps):
|
||||
async with deps.pool.acquire() as conn:
|
||||
rows = await conn.fetch(
|
||||
"""
|
||||
SELECT id, importance, access_count
|
||||
FROM memories
|
||||
ORDER BY importance DESC
|
||||
OFFSET $1
|
||||
""",
|
||||
MAX_DEPTH,
|
||||
)
|
||||
for row in rows:
|
||||
await conn.execute("DELETE FROM memories WHERE id = $1", row["id"])
|
||||
|
||||
|
||||
async def display_memory_tree(deps: Deps) -> str:
|
||||
async with deps.pool.acquire() as conn:
|
||||
rows = await conn.fetch(
|
||||
"""
|
||||
SELECT content, summary, importance, access_count
|
||||
FROM memories
|
||||
ORDER BY importance DESC
|
||||
LIMIT $1
|
||||
""",
|
||||
MAX_DEPTH,
|
||||
)
|
||||
result = ""
|
||||
for row in rows:
|
||||
effective_importance = row["importance"] * (1 + math.log(row["access_count"] + 1))
|
||||
summary = row["summary"] or row["content"]
|
||||
result += f"- {summary} (Importance: {effective_importance:.2f})\n"
|
||||
return result
|
||||
|
||||
|
||||
@mcp.tool()
|
||||
async def remember(
|
||||
contents: list[str] = Field(description="List of observations or memories to store"),
|
||||
):
|
||||
deps = Deps(openai=AsyncOpenAI(), pool=await get_db_pool())
|
||||
try:
|
||||
return "\n".join(await asyncio.gather(*[add_memory(content, deps) for content in contents]))
|
||||
finally:
|
||||
await deps.pool.close()
|
||||
|
||||
|
||||
@mcp.tool()
|
||||
async def read_profile() -> str:
|
||||
deps = Deps(openai=AsyncOpenAI(), pool=await get_db_pool())
|
||||
profile = await display_memory_tree(deps)
|
||||
await deps.pool.close()
|
||||
return profile
|
||||
|
||||
|
||||
async def initialize_database():
|
||||
pool = await asyncpg.create_pool("postgresql://postgres:postgres@localhost:54320/postgres")
|
||||
try:
|
||||
async with pool.acquire() as conn:
|
||||
await conn.execute("""
|
||||
SELECT pg_terminate_backend(pg_stat_activity.pid)
|
||||
FROM pg_stat_activity
|
||||
WHERE pg_stat_activity.datname = 'memory_db'
|
||||
AND pid <> pg_backend_pid();
|
||||
""")
|
||||
await conn.execute("DROP DATABASE IF EXISTS memory_db;")
|
||||
await conn.execute("CREATE DATABASE memory_db;")
|
||||
finally:
|
||||
await pool.close()
|
||||
|
||||
pool = await asyncpg.create_pool(DB_DSN)
|
||||
try:
|
||||
async with pool.acquire() as conn:
|
||||
await conn.execute("CREATE EXTENSION IF NOT EXISTS vector;")
|
||||
|
||||
await register_vector(conn)
|
||||
|
||||
await conn.execute("""
|
||||
CREATE TABLE IF NOT EXISTS memories (
|
||||
id SERIAL PRIMARY KEY,
|
||||
content TEXT NOT NULL,
|
||||
summary TEXT,
|
||||
importance REAL NOT NULL,
|
||||
access_count INT NOT NULL,
|
||||
timestamp DOUBLE PRECISION NOT NULL,
|
||||
embedding vector(1536) NOT NULL
|
||||
);
|
||||
CREATE INDEX IF NOT EXISTS idx_memories_embedding ON memories
|
||||
USING hnsw (embedding vector_l2_ops);
|
||||
""")
|
||||
finally:
|
||||
await pool.close()
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(initialize_database())
|
||||
19
examples/mcpserver/parameter_descriptions.py
Normal file
19
examples/mcpserver/parameter_descriptions.py
Normal file
|
|
@ -0,0 +1,19 @@
|
|||
"""MCPServer Example showing parameter descriptions"""
|
||||
|
||||
from pydantic import Field
|
||||
|
||||
from mcp.server.mcpserver import MCPServer
|
||||
|
||||
# Create server
|
||||
mcp = MCPServer("Parameter Descriptions Server")
|
||||
|
||||
|
||||
@mcp.tool()
|
||||
def greet_user(
|
||||
name: str = Field(description="The name of the person to greet"),
|
||||
title: str = Field(description="Optional title like Mr/Ms/Dr", default=""),
|
||||
times: int = Field(description="Number of times to repeat the greeting", default=1),
|
||||
) -> str:
|
||||
"""Greet a user with optional title and repetition"""
|
||||
greeting = f"Hello {title + ' ' if title else ''}{name}!"
|
||||
return "\n".join([greeting] * times)
|
||||
18
examples/mcpserver/readme-quickstart.py
Normal file
18
examples/mcpserver/readme-quickstart.py
Normal file
|
|
@ -0,0 +1,18 @@
|
|||
from mcp.server.mcpserver import MCPServer
|
||||
|
||||
# Create an MCP server
|
||||
mcp = MCPServer("Demo")
|
||||
|
||||
|
||||
# Add an addition tool
|
||||
@mcp.tool()
|
||||
def sum(a: int, b: int) -> int:
|
||||
"""Add two numbers"""
|
||||
return a + b
|
||||
|
||||
|
||||
# Add a dynamic greeting resource
|
||||
@mcp.resource("greeting://{name}")
|
||||
def get_greeting(name: str) -> str:
|
||||
"""Get a personalized greeting"""
|
||||
return f"Hello, {name}!"
|
||||
27
examples/mcpserver/screenshot.py
Normal file
27
examples/mcpserver/screenshot.py
Normal file
|
|
@ -0,0 +1,27 @@
|
|||
"""MCPServer Screenshot Example
|
||||
|
||||
Give Claude a tool to capture and view screenshots.
|
||||
"""
|
||||
|
||||
import io
|
||||
|
||||
from mcp.server.mcpserver import MCPServer
|
||||
from mcp.server.mcpserver.utilities.types import Image
|
||||
|
||||
# Create server
|
||||
mcp = MCPServer("Screenshot Demo")
|
||||
|
||||
|
||||
@mcp.tool()
|
||||
def take_screenshot() -> Image:
|
||||
"""Take a screenshot of the user's screen and return it as an image. Use
|
||||
this tool anytime the user wants you to look at something they're doing.
|
||||
"""
|
||||
import pyautogui
|
||||
|
||||
buffer = io.BytesIO()
|
||||
|
||||
# if the file exceeds ~1MB, it will be rejected by Claude
|
||||
screenshot = pyautogui.screenshot()
|
||||
screenshot.convert("RGB").save(buffer, format="JPEG", quality=60, optimize=True)
|
||||
return Image(data=buffer.getvalue(), format="jpeg")
|
||||
12
examples/mcpserver/simple_echo.py
Normal file
12
examples/mcpserver/simple_echo.py
Normal file
|
|
@ -0,0 +1,12 @@
|
|||
"""MCPServer Echo Server"""
|
||||
|
||||
from mcp.server.mcpserver import MCPServer
|
||||
|
||||
# Create server
|
||||
mcp = MCPServer("Echo Server")
|
||||
|
||||
|
||||
@mcp.tool()
|
||||
def echo(text: str) -> str:
|
||||
"""Echo the input text"""
|
||||
return text
|
||||
67
examples/mcpserver/text_me.py
Normal file
67
examples/mcpserver/text_me.py
Normal file
|
|
@ -0,0 +1,67 @@
|
|||
# /// script
|
||||
# dependencies = []
|
||||
# ///
|
||||
|
||||
"""MCPServer Text Me Server
|
||||
--------------------------------
|
||||
This defines a simple MCPServer server that sends a text message to a phone number via https://surgemsg.com/.
|
||||
|
||||
To run this example, create a `.env` file with the following values:
|
||||
|
||||
SURGE_API_KEY=...
|
||||
SURGE_ACCOUNT_ID=...
|
||||
SURGE_MY_PHONE_NUMBER=...
|
||||
SURGE_MY_FIRST_NAME=...
|
||||
SURGE_MY_LAST_NAME=...
|
||||
|
||||
Visit https://surgemsg.com/ and click "Get Started" to obtain these values.
|
||||
"""
|
||||
|
||||
from typing import Annotated
|
||||
|
||||
import httpx
|
||||
from pydantic import BeforeValidator
|
||||
from pydantic_settings import BaseSettings, SettingsConfigDict
|
||||
|
||||
from mcp.server.mcpserver import MCPServer
|
||||
|
||||
|
||||
class SurgeSettings(BaseSettings):
|
||||
model_config: SettingsConfigDict = SettingsConfigDict(env_prefix="SURGE_", env_file=".env")
|
||||
|
||||
api_key: str
|
||||
account_id: str
|
||||
my_phone_number: Annotated[str, BeforeValidator(lambda v: "+" + v if not v.startswith("+") else v)]
|
||||
my_first_name: str
|
||||
my_last_name: str
|
||||
|
||||
|
||||
# Create server
|
||||
mcp = MCPServer("Text me")
|
||||
surge_settings = SurgeSettings() # type: ignore
|
||||
|
||||
|
||||
@mcp.tool(name="textme", description="Send a text message to me")
|
||||
def text_me(text_content: str) -> str:
|
||||
"""Send a text message to a phone number via https://surgemsg.com/"""
|
||||
with httpx.Client() as client:
|
||||
response = client.post(
|
||||
"https://api.surgemsg.com/messages",
|
||||
headers={
|
||||
"Authorization": f"Bearer {surge_settings.api_key}",
|
||||
"Surge-Account": surge_settings.account_id,
|
||||
"Content-Type": "application/json",
|
||||
},
|
||||
json={
|
||||
"body": text_content,
|
||||
"conversation": {
|
||||
"contact": {
|
||||
"first_name": surge_settings.my_first_name,
|
||||
"last_name": surge_settings.my_last_name,
|
||||
"phone_number": surge_settings.my_phone_number,
|
||||
}
|
||||
},
|
||||
},
|
||||
)
|
||||
response.raise_for_status()
|
||||
return f"Message sent: {text_content}"
|
||||
59
examples/mcpserver/unicode_example.py
Normal file
59
examples/mcpserver/unicode_example.py
Normal file
|
|
@ -0,0 +1,59 @@
|
|||
"""Example MCPServer server that uses Unicode characters in various places to help test
|
||||
Unicode handling in tools and inspectors.
|
||||
"""
|
||||
|
||||
from mcp.server.mcpserver import MCPServer
|
||||
|
||||
mcp = MCPServer()
|
||||
|
||||
|
||||
@mcp.tool(description="🌟 A tool that uses various Unicode characters in its description: á é í ó ú ñ 漢字 🎉")
|
||||
def hello_unicode(name: str = "世界", greeting: str = "¡Hola") -> str:
|
||||
"""A simple tool that demonstrates Unicode handling in:
|
||||
- Tool description (emojis, accents, CJK characters)
|
||||
- Parameter defaults (CJK characters)
|
||||
- Return values (Spanish punctuation, emojis)
|
||||
"""
|
||||
return f"{greeting}, {name}! 👋"
|
||||
|
||||
|
||||
@mcp.tool(description="🎨 Tool that returns a list of emoji categories")
|
||||
def list_emoji_categories() -> list[str]:
|
||||
"""Returns a list of emoji categories with emoji examples."""
|
||||
return [
|
||||
"😀 Smileys & Emotion",
|
||||
"👋 People & Body",
|
||||
"🐶 Animals & Nature",
|
||||
"🍎 Food & Drink",
|
||||
"⚽ Activities",
|
||||
"🌍 Travel & Places",
|
||||
"💡 Objects",
|
||||
"❤️ Symbols",
|
||||
"🚩 Flags",
|
||||
]
|
||||
|
||||
|
||||
@mcp.tool(description="🔤 Tool that returns text in different scripts")
|
||||
def multilingual_hello() -> str:
|
||||
"""Returns hello in different scripts and writing systems."""
|
||||
return "\n".join(
|
||||
[
|
||||
"English: Hello!",
|
||||
"Spanish: ¡Hola!",
|
||||
"French: Bonjour!",
|
||||
"German: Grüß Gott!",
|
||||
"Russian: Привет!",
|
||||
"Greek: Γεια σας!",
|
||||
"Hebrew: !שָׁלוֹם",
|
||||
"Arabic: !مرحبا",
|
||||
"Hindi: नमस्ते!",
|
||||
"Chinese: 你好!",
|
||||
"Japanese: こんにちは!",
|
||||
"Korean: 안녕하세요!",
|
||||
"Thai: สวัสดี!",
|
||||
]
|
||||
)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
mcp.run()
|
||||
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