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docs: fix stub pages and improve docs structure (#2101)

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Co-authored-by: Max Isbey <224885523+maxisbey@users.noreply.github.com>
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Felix Weinberger 2026-02-23 15:18:24 +00:00 • committed by GitHub
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@ -554,7 +554,7 @@ from mcp.server.fastmcp import FastMCP, Icon
icon = Icon(
src="icon.png",
mimeType="image/png",
sizes="64x64"
sizes=["64x64"]
)
# Add icons to server
@ -576,7 +576,7 @@ def my_resource():
return "content"
```
_Full example: [examples/fastmcp/icons_demo.py](https://github.com/modelcontextprotocol/python-sdk/blob/v1.x/examples/fastmcp/icons_demo.py)_
_Full example: [examples/fastmcp/icons_demo.py](https://github.com/modelcontextprotocol/python-sdk/blob/main/examples/fastmcp/icons_demo.py)_
### Images
@ -973,7 +973,6 @@ The `elicit()` method returns an `ElicitationResult` with:
- `action`: "accept", "decline", or "cancel"
- `data`: The validated response (only when accepted)
- `validation_error`: Any validation error message
#### Elicitation with Enum Values
@ -1007,50 +1006,28 @@ async def pick_color(ctx: Context[ServerSession, None]) -> str:
return "No color selected"
```
#### URL Mode Elicitation
#### Elicitation Complete Notification
URL mode elicitation directs the user to an external URL for out-of-band interactions — for example, entering sensitive data that should not pass through the LLM, or filling out a complex form like a shipping address. The tool call blocks while waiting for the user to complete the interaction:
For URL mode elicitations, send a completion notification after the out-of-band interaction finishes. This tells the client that the elicitation is done and it may retry any blocked requests:
```python
import asyncio
import uuid
import anyio
from mcp.server.fastmcp import Context, FastMCP
from mcp.server.session import ServerSession
mcp = FastMCP("Shipping Example")
# Simulates a database that the web form writes to on submit
completed_elicitations: dict[str, dict] = {}
mcp = FastMCP("Elicit Complete Example")
@mcp.tool()
async def place_order(item: str, ctx: Context[ServerSession, None]) -> str:
"""Place an order (shipping details collected via secure form)."""
elicitation_id = str(uuid.uuid4())
async def handle_oauth_callback(
elicitation_id: str, ctx: Context[ServerSession, None]
) -> str:
"""Called when OAuth flow completes out-of-band."""
# ... process the callback ...
# Direct the user to a form to enter their shipping address
result = await ctx.elicit_url(
message=f"Please enter your shipping details for '{item}'.",
url=f"https://example.com/shipping?id={elicitation_id}",
elicitation_id=elicitation_id,
)
if result.action != "accept":
return "Order cancelled."
# Poll until the shipping form is submitted
with anyio.fail_after(120):
while elicitation_id not in completed_elicitations:
await asyncio.sleep(1)
# Notify the client that the out-of-band interaction is done
# Notify the client that the elicitation is done
await ctx.session.send_elicit_complete(elicitation_id)
shipping = completed_elicitations.pop(elicitation_id)
return f"Order placed! Shipping '{item}' to {shipping['address']}"
return "Authorization complete"
```
### Sampling
@ -1144,75 +1121,7 @@ When this handler is registered, the server automatically declares the `logging`
### Authentication
Authentication can be used by servers that want to expose tools accessing protected resources.
`mcp.server.auth` implements OAuth 2.1 resource server functionality, where MCP servers act as Resource Servers (RS) that validate tokens issued by separate Authorization Servers (AS). This follows the [MCP authorization specification](https://modelcontextprotocol.io/specification/2025-06-18/basic/authorization) and implements RFC 9728 (Protected Resource Metadata) for AS discovery.
MCP servers can use authentication by providing an implementation of the `TokenVerifier` protocol:
<!-- snippet-source examples/snippets/servers/oauth_server.py -->
```python
"""
Run from the repository root:
uv run examples/snippets/servers/oauth_server.py
"""
from pydantic import AnyHttpUrl
from mcp.server.auth.provider import AccessToken, TokenVerifier
from mcp.server.auth.settings import AuthSettings
from mcp.server.fastmcp import FastMCP
class SimpleTokenVerifier(TokenVerifier):
"""Simple token verifier for demonstration."""
async def verify_token(self, token: str) -> AccessToken | None:
pass # This is where you would implement actual token validation
# Create FastMCP instance as a Resource Server
mcp = FastMCP(
"Weather Service",
json_response=True,
# Token verifier for authentication
token_verifier=SimpleTokenVerifier(),
# Auth settings for RFC 9728 Protected Resource Metadata
auth=AuthSettings(
issuer_url=AnyHttpUrl("https://auth.example.com"), # Authorization Server URL
resource_server_url=AnyHttpUrl("http://localhost:3001"), # This server's URL
required_scopes=["user"],
),
)
@mcp.tool()
async def get_weather(city: str = "London") -> dict[str, str]:
"""Get weather data for a city"""
return {
"city": city,
"temperature": "22",
"condition": "Partly cloudy",
"humidity": "65%",
}
if __name__ == "__main__":
mcp.run(transport="streamable-http")
```
_Full example: [examples/snippets/servers/oauth_server.py](https://github.com/modelcontextprotocol/python-sdk/blob/main/examples/snippets/servers/oauth_server.py)_
<!-- /snippet-source -->
For a complete example with separate Authorization Server and Resource Server implementations, see [`examples/servers/simple-auth/`](../examples/servers/simple-auth/).
**Architecture:**
- **Authorization Server (AS)**: Handles OAuth flows, user authentication, and token issuance
- **Resource Server (RS)**: Your MCP server that validates tokens and serves protected resources
- **Client**: Discovers AS through RFC 9728, obtains tokens, and uses them with the MCP server
See [TokenVerifier](../src/mcp/server/auth/provider.py) for more details on implementing token validation.
For OAuth 2.1 server and client authentication, see [Authorization](authorization.md).
### FastMCP Properties
@ -1492,8 +1401,8 @@ _Full example: [examples/snippets/servers/streamable_starlette_mount.py](https:/
For low level server with Streamable HTTP implementations, see:
- Stateful server: [`examples/servers/simple-streamablehttp/`](../examples/servers/simple-streamablehttp/)
- Stateless server: [`examples/servers/simple-streamablehttp-stateless/`](../examples/servers/simple-streamablehttp-stateless/)
- Stateful server: [`examples/servers/simple-streamablehttp/`](examples/servers/simple-streamablehttp/)
- Stateless server: [`examples/servers/simple-streamablehttp-stateless/`](examples/servers/simple-streamablehttp-stateless/)
The streamable HTTP transport supports:
@ -1739,7 +1648,7 @@ _Full example: [examples/snippets/servers/streamable_http_path_config.py](https:
#### SSE servers
> **Note**: SSE transport is being superseded by [Streamable HTTP transport](https://modelcontextprotocol.io/specification/2025-03-26/basic/transports#streamable-http).
> **Note**: SSE transport is being superseded by [Streamable HTTP transport](https://modelcontextprotocol.io/specification/2025-11-25/basic/transports#streamable-http).
You can mount the SSE server to an existing ASGI server using the `sse_app` method. This allows you to integrate the SSE server with other ASGI applications.
@ -1803,489 +1712,4 @@ For more information on mounting applications in Starlette, see the [Starlette d
## Advanced Usage
### Low-Level Server
For more control, you can use the low-level server implementation directly. This gives you full access to the protocol and allows you to customize every aspect of your server, including lifecycle management through the lifespan API:
<!-- snippet-source examples/snippets/servers/lowlevel/lifespan.py -->
```python
"""
Run from the repository root:
uv run examples/snippets/servers/lowlevel/lifespan.py
"""
from collections.abc import AsyncIterator
from contextlib import asynccontextmanager
from typing import Any
import mcp.server.stdio
import mcp.types as types
from mcp.server.lowlevel import NotificationOptions, Server
from mcp.server.models import InitializationOptions
# Mock database class for example
class Database:
"""Mock database class for example."""
@classmethod
async def connect(cls) -> "Database":
"""Connect to database."""
print("Database connected")
return cls()
async def disconnect(self) -> None:
"""Disconnect from database."""
print("Database disconnected")
async def query(self, query_str: str) -> list[dict[str, str]]:
"""Execute a query."""
# Simulate database query
return [{"id": "1", "name": "Example", "query": query_str}]
@asynccontextmanager
async def server_lifespan(_server: Server) -> AsyncIterator[dict[str, Any]]:
"""Manage server startup and shutdown lifecycle."""
# Initialize resources on startup
db = await Database.connect()
try:
yield {"db": db}
finally:
# Clean up on shutdown
await db.disconnect()
# Pass lifespan to server
server = Server("example-server", lifespan=server_lifespan)
@server.list_tools()
async def handle_list_tools() -> list[types.Tool]:
"""List available tools."""
return [
types.Tool(
name="query_db",
description="Query the database",
inputSchema={
"type": "object",
"properties": {"query": {"type": "string", "description": "SQL query to execute"}},
"required": ["query"],
},
)
]
@server.call_tool()
async def query_db(name: str, arguments: dict[str, Any]) -> list[types.TextContent]:
"""Handle database query tool call."""
if name != "query_db":
raise ValueError(f"Unknown tool: {name}")
# Access lifespan context
ctx = server.request_context
db = ctx.lifespan_context["db"]
# Execute query
results = await db.query(arguments["query"])
return [types.TextContent(type="text", text=f"Query results: {results}")]
async def run():
"""Run the server with lifespan management."""
async with mcp.server.stdio.stdio_server() as (read_stream, write_stream):
await server.run(
read_stream,
write_stream,
InitializationOptions(
server_name="example-server",
server_version="0.1.0",
capabilities=server.get_capabilities(
notification_options=NotificationOptions(),
experimental_capabilities={},
),
),
)
if __name__ == "__main__":
import asyncio
asyncio.run(run())
```
_Full example: [examples/snippets/servers/lowlevel/lifespan.py](https://github.com/modelcontextprotocol/python-sdk/blob/main/examples/snippets/servers/lowlevel/lifespan.py)_
<!-- /snippet-source -->
The lifespan API provides:
- A way to initialize resources when the server starts and clean them up when it stops
- Access to initialized resources through the request context in handlers
- Type-safe context passing between lifespan and request handlers
<!-- snippet-source examples/snippets/servers/lowlevel/basic.py -->
```python
"""
Run from the repository root:
uv run examples/snippets/servers/lowlevel/basic.py
"""
import asyncio
import mcp.server.stdio
import mcp.types as types
from mcp.server.lowlevel import NotificationOptions, Server
from mcp.server.models import InitializationOptions
# Create a server instance
server = Server("example-server")
@server.list_prompts()
async def handle_list_prompts() -> list[types.Prompt]:
"""List available prompts."""
return [
types.Prompt(
name="example-prompt",
description="An example prompt template",
arguments=[types.PromptArgument(name="arg1", description="Example argument", required=True)],
)
]
@server.get_prompt()
async def handle_get_prompt(name: str, arguments: dict[str, str] | None) -> types.GetPromptResult:
"""Get a specific prompt by name."""
if name != "example-prompt":
raise ValueError(f"Unknown prompt: {name}")
arg1_value = (arguments or {}).get("arg1", "default")
return types.GetPromptResult(
description="Example prompt",
messages=[
types.PromptMessage(
role="user",
content=types.TextContent(type="text", text=f"Example prompt text with argument: {arg1_value}"),
)
],
)
async def run():
"""Run the basic low-level server."""
async with mcp.server.stdio.stdio_server() as (read_stream, write_stream):
await server.run(
read_stream,
write_stream,
InitializationOptions(
server_name="example",
server_version="0.1.0",
capabilities=server.get_capabilities(
notification_options=NotificationOptions(),
experimental_capabilities={},
),
),
)
if __name__ == "__main__":
asyncio.run(run())
```
_Full example: [examples/snippets/servers/lowlevel/basic.py](https://github.com/modelcontextprotocol/python-sdk/blob/main/examples/snippets/servers/lowlevel/basic.py)_
<!-- /snippet-source -->
Caution: The `uv run mcp run` and `uv run mcp dev` tool doesn't support low-level server.
#### Structured Output Support
The low-level server supports structured output for tools, allowing you to return both human-readable content and machine-readable structured data. Tools can define an `outputSchema` to validate their structured output:
<!-- snippet-source examples/snippets/servers/lowlevel/structured_output.py -->
```python
"""
Run from the repository root:
uv run examples/snippets/servers/lowlevel/structured_output.py
"""
import asyncio
from typing import Any
import mcp.server.stdio
import mcp.types as types
from mcp.server.lowlevel import NotificationOptions, Server
from mcp.server.models import InitializationOptions
server = Server("example-server")
@server.list_tools()
async def list_tools() -> list[types.Tool]:
"""List available tools with structured output schemas."""
return [
types.Tool(
name="get_weather",
description="Get current weather for a city",
inputSchema={
"type": "object",
"properties": {"city": {"type": "string", "description": "City name"}},
"required": ["city"],
},
outputSchema={
"type": "object",
"properties": {
"temperature": {"type": "number", "description": "Temperature in Celsius"},
"condition": {"type": "string", "description": "Weather condition"},
"humidity": {"type": "number", "description": "Humidity percentage"},
"city": {"type": "string", "description": "City name"},
},
"required": ["temperature", "condition", "humidity", "city"],
},
)
]
@server.call_tool()
async def call_tool(name: str, arguments: dict[str, Any]) -> dict[str, Any]:
"""Handle tool calls with structured output."""
if name == "get_weather":
city = arguments["city"]
# Simulated weather data - in production, call a weather API
weather_data = {
"temperature": 22.5,
"condition": "partly cloudy",
"humidity": 65,
"city": city, # Include the requested city
}
# low-level server will validate structured output against the tool's
# output schema, and additionally serialize it into a TextContent block
# for backwards compatibility with pre-2025-06-18 clients.
return weather_data
else:
raise ValueError(f"Unknown tool: {name}")
async def run():
"""Run the structured output server."""
async with mcp.server.stdio.stdio_server() as (read_stream, write_stream):
await server.run(
read_stream,
write_stream,
InitializationOptions(
server_name="structured-output-example",
server_version="0.1.0",
capabilities=server.get_capabilities(
notification_options=NotificationOptions(),
experimental_capabilities={},
),
),
)
if __name__ == "__main__":
asyncio.run(run())
```
_Full example: [examples/snippets/servers/lowlevel/structured_output.py](https://github.com/modelcontextprotocol/python-sdk/blob/main/examples/snippets/servers/lowlevel/structured_output.py)_
<!-- /snippet-source -->
Tools can return data in four ways:
1. **Content only**: Return a list of content blocks (default behavior before spec revision 2025-06-18)
2. **Structured data only**: Return a dictionary that will be serialized to JSON (Introduced in spec revision 2025-06-18)
3. **Both**: Return a tuple of (content, structured_data) preferred option to use for backwards compatibility
4. **Direct CallToolResult**: Return `CallToolResult` directly for full control (including `_meta` field)
When an `outputSchema` is defined, the server automatically validates the structured output against the schema. This ensures type safety and helps catch errors early.
##### Returning CallToolResult Directly
For full control over the response including the `_meta` field (for passing data to client applications without exposing it to the model), return `CallToolResult` directly:
<!-- snippet-source examples/snippets/servers/lowlevel/direct_call_tool_result.py -->
```python
"""
Run from the repository root:
uv run examples/snippets/servers/lowlevel/direct_call_tool_result.py
"""
import asyncio
from typing import Any
import mcp.server.stdio
import mcp.types as types
from mcp.server.lowlevel import NotificationOptions, Server
from mcp.server.models import InitializationOptions
server = Server("example-server")
@server.list_tools()
async def list_tools() -> list[types.Tool]:
"""List available tools."""
return [
types.Tool(
name="advanced_tool",
description="Tool with full control including _meta field",
inputSchema={
"type": "object",
"properties": {"message": {"type": "string"}},
"required": ["message"],
},
)
]
@server.call_tool()
async def handle_call_tool(name: str, arguments: dict[str, Any]) -> types.CallToolResult:
"""Handle tool calls by returning CallToolResult directly."""
if name == "advanced_tool":
message = str(arguments.get("message", ""))
return types.CallToolResult(
content=[types.TextContent(type="text", text=f"Processed: {message}")],
structuredContent={"result": "success", "message": message},
_meta={"hidden": "data for client applications only"},
)
raise ValueError(f"Unknown tool: {name}")
async def run():
"""Run the server."""
async with mcp.server.stdio.stdio_server() as (read_stream, write_stream):
await server.run(
read_stream,
write_stream,
InitializationOptions(
server_name="example",
server_version="0.1.0",
capabilities=server.get_capabilities(
notification_options=NotificationOptions(),
experimental_capabilities={},
),
),
)
if __name__ == "__main__":
asyncio.run(run())
```
_Full example: [examples/snippets/servers/lowlevel/direct_call_tool_result.py](https://github.com/modelcontextprotocol/python-sdk/blob/main/examples/snippets/servers/lowlevel/direct_call_tool_result.py)_
<!-- /snippet-source -->
**Note:** When returning `CallToolResult`, you bypass the automatic content/structured conversion. You must construct the complete response yourself.
### Pagination (Advanced)
For servers that need to handle large datasets, the low-level server provides paginated versions of list operations. This is an optional optimization - most servers won't need pagination unless they're dealing with hundreds or thousands of items.
#### Server-side Implementation
<!-- snippet-source examples/snippets/servers/pagination_example.py -->
```python
"""
Example of implementing pagination with MCP server decorators.
"""
from pydantic import AnyUrl
import mcp.types as types
from mcp.server.lowlevel import Server
# Initialize the server
server = Server("paginated-server")
# Sample data to paginate
ITEMS = [f"Item {i}" for i in range(1, 101)] # 100 items
@server.list_resources()
async def list_resources_paginated(request: types.ListResourcesRequest) -> types.ListResourcesResult:
"""List resources with pagination support."""
page_size = 10
# Extract cursor from request params
cursor = request.params.cursor if request.params is not None else None
# Parse cursor to get offset
start = 0 if cursor is None else int(cursor)
end = start + page_size
# Get page of resources
page_items = [
types.Resource(uri=AnyUrl(f"resource://items/{item}"), name=item, description=f"Description for {item}")
for item in ITEMS[start:end]
]
# Determine next cursor
next_cursor = str(end) if end < len(ITEMS) else None
return types.ListResourcesResult(resources=page_items, nextCursor=next_cursor)
```
_Full example: [examples/snippets/servers/pagination_example.py](https://github.com/modelcontextprotocol/python-sdk/blob/main/examples/snippets/servers/pagination_example.py)_
<!-- /snippet-source -->
#### Client-side Consumption
<!-- snippet-source examples/snippets/clients/pagination_client.py -->
```python
"""
Example of consuming paginated MCP endpoints from a client.
"""
import asyncio
from mcp.client.session import ClientSession
from mcp.client.stdio import StdioServerParameters, stdio_client
from mcp.types import PaginatedRequestParams, Resource
async def list_all_resources() -> None:
"""Fetch all resources using pagination."""
async with stdio_client(StdioServerParameters(command="uv", args=["run", "mcp-simple-pagination"])) as (
read,
write,
):
async with ClientSession(read, write) as session:
await session.initialize()
all_resources: list[Resource] = []
cursor = None
while True:
# Fetch a page of resources
result = await session.list_resources(params=PaginatedRequestParams(cursor=cursor))
all_resources.extend(result.resources)
print(f"Fetched {len(result.resources)} resources")
# Check if there are more pages
if result.nextCursor:
cursor = result.nextCursor
else:
break
print(f"Total resources: {len(all_resources)}")
if __name__ == "__main__":
asyncio.run(list_all_resources())
```
_Full example: [examples/snippets/clients/pagination_client.py](https://github.com/modelcontextprotocol/python-sdk/blob/main/examples/snippets/clients/pagination_client.py)_
<!-- /snippet-source -->
#### Key Points
- **Cursors are opaque strings** - the server defines the format (numeric offsets, timestamps, etc.)
- **Return `nextCursor=None`** when there are no more pages
- **Backward compatible** - clients that don't support pagination will still work (they'll just get the first page)
- **Flexible page sizes** - Each endpoint can define its own page size based on data characteristics
See the [simple-pagination example](../examples/servers/simple-pagination) for a complete implementation.
For the low-level server API, pagination, and direct handler registration, see [Low-Level Server](low-level-server.md).