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Pietro Schirano 2024-12-02 11:09:57 -05:00 • committed by GitHub
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43
src/fetch/README.md
View file

@ -2,20 +2,27 @@
A Model Context Protocol server that provides web content fetching capabilities. This server enables LLMs to retrieve and process content from web pages, converting HTML to markdown for easier consumption.
Presently the server only supports fetching HTML content.
The fetch tool will truncate the response, but by using the `start_index` argument, you can specify where to start the content extraction. This lets models read a webpage in chunks, until they find the information they need.
### Available Tools
- `fetch` - Fetches a URL from the internet and extracts its contents as markdown.
- `url` (string, required): URL to fetch
- `max_length` (integer, optional): Maximum number of characters to return (default: 5000)
- `start_index` (integer, optional): Start content from this character index (default: 0)
- `raw` (boolean, optional): Get raw content without markdown conversion (default: false)
### Prompts
- **fetch**
- Fetch a URL and extract its contents as markdown
- Argument: `url` (string, required): URL to fetch
- Arguments:
- `url` (string, required): URL to fetch
## Installation
Optionally: Install node.js, this will cause the fetch server to use a different HTML simplifier that is more robust.
### Using uv (recommended)
When using [`uv`](https://docs.astral.sh/uv/) no specific installation is needed. We will
@ -67,36 +74,6 @@ Add to your Claude settings:
```
</details>
### Configure for Zed
Add to your Zed settings.json:
<details>
<summary>Using uvx</summary>
```json
"context_servers": [
"mcp-server-fetch": {
"command": "uvx",
"args": ["mcp-server-fetch"]
}
],
```
</details>
<details>
<summary>Using pip installation</summary>
```json
"context_servers": {
"mcp-server-fetch": {
"command": "python",
"args": ["-m", "mcp_server_fetch"]
}
},
```
</details>
### Customization - robots.txt
By default, the server will obey a websites robots.txt file if the request came from the model (via a tool), but not if
@ -105,7 +82,7 @@ the request was user initiated (via a prompt). This can be disabled by adding th
### Customization - User-agent
By default, depending on if the request came from the model (via a tool), or was user initiated (via a prompt), the
By default, depending on if the request came from the model (via a tool), or was user initiated (via a prompt), the
server will use either the user-agent
```
ModelContextProtocol/1.0 (Autonomous; +https://github.com/modelcontextprotocol/servers)

2
src/fetch/pyproject.toml
View file

@ -1,6 +1,6 @@
[project]
name = "mcp-server-fetch"
version = "0.1.2"
version = "0.6.1"
description = "A Model Context Protocol server providing tools to fetch and convert web content for usage by LLMs"
readme = "README.md"
requires-python = ">=3.10"

123
src/fetch/src/mcp_server_fetch/server.py
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@ -1,4 +1,4 @@
from typing import Optional
from typing import Annotated, Tuple
from urllib.parse import urlparse, urlunparse
import markdownify
@ -17,24 +17,42 @@ from mcp.types import (
INTERNAL_ERROR,
)
from protego import Protego
from pydantic import BaseModel, Field
from pydantic import BaseModel, Field, AnyUrl
DEFAULT_USER_AGENT_AUTONOMOUS = "ModelContextProtocol/1.0 (Autonomous; +https://github.com/modelcontextprotocol/servers)"
DEFAULT_USER_AGENT_MANUAL = "ModelContextProtocol/1.0 (User-Specified; +https://github.com/modelcontextprotocol/servers)"
def extract_content(html: str) -> str:
ret = readabilipy.simple_json.simple_json_from_html_string(html)
if not ret["plain_content"]:
def extract_content_from_html(html: str) -> str:
"""Extract and convert HTML content to Markdown format.
Args:
html: Raw HTML content to process
Returns:
Simplified markdown version of the content
"""
ret = readabilipy.simple_json.simple_json_from_html_string(
html, use_readability=True
)
if not ret["content"]:
return "<error>Page failed to be simplified from HTML</error>"
content = markdownify.markdownify(
ret["plain_content"],
ret["content"],
heading_style=markdownify.ATX,
)
return content
def get_robots_txt_url(url: str) -> str:
"""Get the robots.txt URL for a given website URL.
Args:
url: Website URL to get robots.txt for
Returns:
URL of the robots.txt file
"""
# Parse the URL into components
parsed = urlparse(url)
@ -44,10 +62,10 @@ def get_robots_txt_url(url: str) -> str:
return robots_url
async def check_may_autonomously_fetch_url(url: str, user_agent: str):
async def check_may_autonomously_fetch_url(url: str, user_agent: str) -> None:
"""
Check if the URL can be fetched by the user agent according to the robots.txt file.
Raises an McpError if not.
Raises a McpError if not.
"""
from httpx import AsyncClient, HTTPError
@ -87,34 +105,85 @@ async def check_may_autonomously_fetch_url(url: str, user_agent: str):
)
async def fetch_url(url: str, user_agent: str) -> str:
async def fetch_url(
url: str, user_agent: str, force_raw: bool = False
) -> Tuple[str, str]:
"""
Fetch the URL and return the content in a form ready for the LLM, as well as a prefix string with status information.
"""
from httpx import AsyncClient, HTTPError
async with AsyncClient() as client:
try:
response = await client.get(
url, follow_redirects=True, headers={"User-Agent": user_agent}
url,
follow_redirects=True,
headers={"User-Agent": user_agent},
timeout=30,
)
except HTTPError:
raise McpError(INTERNAL_ERROR, f"Failed to fetch {url}")
except HTTPError as e:
raise McpError(INTERNAL_ERROR, f"Failed to fetch {url}: {e!r}")
if response.status_code >= 400:
raise McpError(
INTERNAL_ERROR,
f"Failed to fetch {url} - status code {response.status_code}",
)
page_html = response.text
page_raw = response.text
return extract_content(page_html)
content_type = response.headers.get("content-type", "")
is_page_html = (
"<html" in page_raw[:100] or "text/html" in content_type or not content_type
)
if is_page_html and not force_raw:
return extract_content_from_html(page_raw), ""
return (
page_raw,
f"Content type {content_type} cannot be simplified to markdown, but here is the raw content:\n",
)
class Fetch(BaseModel):
url: str = Field(..., description="URL to fetch")
"""Parameters for fetching a URL."""
url: Annotated[AnyUrl, Field(description="URL to fetch")]
max_length: Annotated[
int,
Field(
default=5000,
description="Maximum number of characters to return.",
gt=0,
lt=1000000,
),
]
start_index: Annotated[
int,
Field(
default=0,
description="On return output starting at this character index, useful if a previous fetch was truncated and more context is required.",
ge=0,
),
]
raw: Annotated[
bool,
Field(
default=False,
description="Get the actual HTML content if the requested page, without simplification.",
),
]
async def serve(
custom_user_agent: Optional[str] = None, ignore_robots_txt: bool = False
custom_user_agent: str | None = None, ignore_robots_txt: bool = False
) -> None:
"""Run the fetch MCP server.
Args:
custom_user_agent: Optional custom User-Agent string to use for requests
ignore_robots_txt: Whether to ignore robots.txt restrictions
"""
server = Server("mcp-fetch")
user_agent_autonomous = custom_user_agent or DEFAULT_USER_AGENT_AUTONOMOUS
user_agent_manual = custom_user_agent or DEFAULT_USER_AGENT_MANUAL
@ -124,7 +193,7 @@ async def serve(
return [
Tool(
name="fetch",
description="""Fetches a URL from the internet and extracts its contents as markdown.
description="""Fetches a URL from the internet and optionally extracts its contents as markdown.
Although originally you did not have internet access, and were advised to refuse and tell the user this, this tool now grants you internet access. Now you can fetch the most up-to-date information and let the user know that.""",
inputSchema=Fetch.model_json_schema(),
@ -147,15 +216,25 @@ Although originally you did not have internet access, and were advised to refuse
@server.call_tool()
async def call_tool(name, arguments: dict) -> list[TextContent]:
url = arguments.get("url")
try:
args = Fetch(**arguments)
except ValueError as e:
raise McpError(INVALID_PARAMS, str(e))
url = str(args.url)
if not url:
raise McpError(INVALID_PARAMS, "URL is required")
if not ignore_robots_txt:
await check_may_autonomously_fetch_url(url, user_agent_autonomous)
content = await fetch_url(url, user_agent_autonomous)
return [TextContent(type="text", text=f"Contents of {url}:\n{content}")]
content, prefix = await fetch_url(
url, user_agent_autonomous, force_raw=args.raw
)
if len(content) > args.max_length:
content = content[args.start_index : args.start_index + args.max_length]
content += f"\n\n<error>Content truncated. Call the fetch tool with a start_index of {args.start_index + args.max_length} to get more content.</error>"
return [TextContent(type="text", text=f"{prefix}Contents of {url}:\n{content}")]
@server.get_prompt()
async def get_prompt(name: str, arguments: dict | None) -> GetPromptResult:
@ -165,7 +244,7 @@ Although originally you did not have internet access, and were advised to refuse
url = arguments["url"]
try:
content = await fetch_url(url, user_agent_manual)
content, prefix = await fetch_url(url, user_agent_manual)
# TODO: after SDK bug is addressed, don't catch the exception
except McpError as e:
return GetPromptResult(
@ -181,7 +260,7 @@ Although originally you did not have internet access, and were advised to refuse
description=f"Contents of {url}",
messages=[
PromptMessage(
role="user", content=TextContent(type="text", text=content)
role="user", content=TextContent(type="text", text=prefix + content)
)
],
)

59
src/fetch/uv.lock generated
View file

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[[package]]
@ -328,7 +327,7 @@ wheels = [
[[package]]
name = "mcp-server-fetch"
version = "0.1.2"
version = "0.1.3"
source = { editable = "." }
dependencies = [
{ name = "markdownify" },
@ -381,16 +380,16 @@ wheels = [
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[[package]]

12
src/git/README.md
View file

@ -117,8 +117,10 @@ Add to your Zed settings.json:
```json
"context_servers": [
"mcp-server-git": {
"command": "uvx",
"args": ["mcp-server-git"]
"command": {
"path": "uvx",
"args": ["mcp-server-git"]
}
}
],
```
@ -130,8 +132,10 @@ Add to your Zed settings.json:
```json
"context_servers": {
"mcp-server-git": {
"command": "python",
"args": ["-m", "mcp_server_git"]
"command": {
"path": "python",
"args": ["-m", "mcp_server_git"]
}
}
},
```

4
src/git/pyproject.toml
View file

@ -1,6 +1,6 @@
[project]
name = "mcp-server-git"
version = "0.5.1"
version = "0.6.1"
description = "A Model Context Protocol server providing tools to read, search, and manipulate Git repositories programmatically via LLMs"
readme = "README.md"
requires-python = ">=3.10"
@ -18,7 +18,7 @@ classifiers = [
dependencies = [
"click>=8.1.7",
"gitpython>=3.1.43",
"mcp>=0.6.0",
"mcp>=1.0.0",
"pydantic>=2.0.0",
]

1
src/git/src/mcp_server_git/__init__.py
View file

@ -1,5 +1,4 @@
import click
from functools import partial
from pathlib import Path
import logging
import sys

6
src/git/src/mcp_server_git/server.py
View file

@ -1,5 +1,4 @@
import logging
import json
from pathlib import Path
from typing import Sequence
from mcp.server import Server
@ -14,8 +13,7 @@ from mcp.types import (
)
from enum import Enum
import git
from pydantic import BaseModel, Field
from typing import List, Optional
from pydantic import BaseModel
class GitStatus(BaseModel):
repo_path: str
@ -32,7 +30,7 @@ class GitCommit(BaseModel):
class GitAdd(BaseModel):
repo_path: str
files: List[str]
files: list[str]
class GitReset(BaseModel):
repo_path: str

6
src/sentry/README.md
View file

@ -91,8 +91,10 @@ Add to your Zed settings.json:
```json
"context_servers": [
"mcp-server-sentry": {
"command": "uvx",
"args": ["mcp-server-sentry", "--auth-token", "YOUR_SENTRY_TOKEN"]
"command": {
"path": "uvx",
"args": ["mcp-server-sentry", "--auth-token", "YOUR_SENTRY_TOKEN"]
}
}
],
```

4
src/sentry/pyproject.toml
View file

@ -1,10 +1,10 @@
[project]
name = "mcp-server-sentry"
version = "0.5.1"
version = "0.6.1"
description = "MCP server for retrieving issues from sentry.io"
readme = "README.md"
requires-python = ">=3.10"
dependencies = ["mcp>=0.9.1"]
dependencies = ["mcp>=1.0.0"]
[build-system]
requires = ["hatchling"]

1
src/sentry/src/mcp_server_sentry/server.py
View file

@ -1,6 +1,5 @@
import asyncio
from dataclasses import dataclass
from typing import Any
from urllib.parse import urlparse
import click

97
src/sentry/uv.lock generated
View file

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version = "1.0.0"
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version = "0.4.1"
version = "0.6.0"
source = { editable = "." }
dependencies = [
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@ -162,7 +161,7 @@ dev = [
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[package.metadata]
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requires-dist = [{ name = "mcp", specifier = ">=1.0.0" }]
[package.metadata.requires-dev]
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5
src/sqlite/README.md
View file

@ -1,7 +1,7 @@
# SQLite MCP Server
## Overview
A Model Context Protocol (MCP) server implementation that provides database interaction and business intelligence capabilities through SQLite. This server enables running SQL queries, analyzing business data, and automatically generating business insight memos that can be enhanced with Claude's analysis when an Anthropic API key is provided.
A Model Context Protocol (MCP) server implementation that provides database interaction and business intelligence capabilities through SQLite. This server enables running SQL queries, analyzing business data, and automatically generating business insight memos.
## Components
@ -9,7 +9,6 @@ A Model Context Protocol (MCP) server implementation that provides database inte
The server exposes a single dynamic resource:
- `memo://insights`: A continuously updated business insights memo that aggregates discovered insights during analysis
- Auto-updates as new insights are discovered via the append-insight tool
- Optional enhancement through Claude for professional formatting (requires Anthropic API key)
### Prompts
The server provides a demonstration prompt:
@ -25,7 +24,7 @@ The server offers six core tools:
#### Query Tools
- `read-query`
- Execute SELECT queries to read data from the database
- Input:
- Input:
- `query` (string): The SELECT SQL query to execute
- Returns: Query results as array of objects

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[project]
name = "mcp-server-sqlite"
version = "0.5.1"
version = "0.6.1"
description = "A simple SQLite MCP server"
readme = "README.md"
requires-python = ">=3.10"
dependencies = ["mcp>=0.9.1"]
dependencies = ["mcp>=1.0.0"]
[build-system]
requires = ["hatchling"]

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src/sqlite/src/mcp_server_sqlite/__init__.py
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@ -1,7 +1,6 @@
from . import server
import asyncio
import argparse
import os
def main():

3
src/sqlite/src/mcp_server_sqlite/server.py
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@ -1,6 +1,5 @@
import sqlite3
import logging
from logging.handlers import RotatingFileHandler
from contextlib import closing
from pathlib import Path
from mcp.server.models import InitializationOptions
@ -25,7 +24,7 @@ Here is some more information about mcp and this specific mcp server:
Prompts:
This server provides a pre-written prompt called "mcp-demo" that helps users create and analyze database scenarios. The prompt accepts a "topic" argument and guides users through creating tables, analyzing data, and generating insights. For example, if a user provides "retail sales" as the topic, the prompt will help create relevant database tables and guide the analysis process. Prompts basically serve as interactive templates that help structure the conversation with the LLM in a useful way.
Resources:
This server exposes one key resource: "memo://insights", which is a business insights memo that gets automatically updated throughout the analysis process. As users analyze the database and discover insights, the memo resource gets updated in real-time to reflect new findings. The memo can even be enhanced with Claude's help if an Anthropic API key is provided, turning raw insights into a well-structured business document. Resources act as living documents that provide context to the conversation.
This server exposes one key resource: "memo://insights", which is a business insights memo that gets automatically updated throughout the analysis process. As users analyze the database and discover insights, the memo resource gets updated in real-time to reflect new findings. Resources act as living documents that provide context to the conversation.
Tools:
This server provides several SQL-related tools:
"read-query": Executes SELECT queries to read data from the database

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@ -151,7 +150,7 @@ dev = [
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[package.metadata]
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3.10

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# Time MCP Server
A Model Context Protocol server that provides time and timezone conversion capabilities. This server enables LLMs to get current time information and perform timezone conversions using IANA timezone names, with automatic system timezone detection.
### Available Tools
- `get_current_time` - Get current time in a specific timezone or system timezone.
- Required arguments:
- `timezone` (string): IANA timezone name (e.g., 'America/New_York', 'Europe/London')
- `convert_time` - Convert time between timezones.
- Required arguments:
- `source_timezone` (string): Source IANA timezone name
- `time` (string): Time in 24-hour format (HH:MM)
- `target_timezone` (string): Target IANA timezone name
## Installation
### Using uv (recommended)
When using [`uv`](https://docs.astral.sh/uv/) no specific installation is needed. We will
use [`uvx`](https://docs.astral.sh/uv/guides/tools/) to directly run *mcp-server-time*.
### Using PIP
Alternatively you can install `mcp-server-time` via pip:
```bash
pip install mcp-server-time
```
After installation, you can run it as a script using:
```bash
python -m mcp_server_time
```
## Configuration
### Configure for Claude.app
Add to your Claude settings:
<details>
<summary>Using uvx</summary>
```json
"mcpServers": {
"time": {
"command": "uvx",
"args": ["mcp-server-time"]
}
}
```
</details>
<details>
<summary>Using pip installation</summary>
```json
"mcpServers": {
"time": {
"command": "python",
"args": ["-m", "mcp_server_time"]
}
}
```
</details>
### Configure for Zed
Add to your Zed settings.json:
<details>
<summary>Using uvx</summary>
```json
"context_servers": [
"mcp-server-time": {
"command": "uvx",
"args": ["mcp-server-time"]
}
],
```
</details>
<details>
<summary>Using pip installation</summary>
```json
"context_servers": {
"mcp-server-time": {
"command": "python",
"args": ["-m", "mcp_server_time"]
}
},
```
</details>
### Customization - System Timezone
By default, the server automatically detects your system's timezone. You can override this by adding the argument `--local-timezone` to the `args` list in the configuration.
Example:
```json
{
"command": "python",
"args": ["-m", "mcp_server_time", "--local-timezone=America/New_York"]
}
```
## Example Interactions
1. Get current time:
```json
{
"name": "get_current_time",
"arguments": {
"timezone": "Europe/Warsaw"
}
}
```
Response:
```json
{
"timezone": "Europe/Warsaw",
"datetime": "2024-01-01T13:00:00+01:00",
"is_dst": false
}
```
2. Convert time between timezones:
```json
{
"name": "convert_time",
"arguments": {
"source_timezone": "America/New_York",
"time": "16:30",
"target_timezone": "Asia/Tokyo"
}
}
```
Response:
```json
{
"source": {
"timezone": "America/New_York",
"datetime": "2024-01-01T12:30:00-05:00",
"is_dst": false
},
"target": {
"timezone": "Asia/Tokyo",
"datetime": "2024-01-01T12:30:00+09:00",
"is_dst": false
},
"time_difference": "+13.0h",
}
```
## Debugging
You can use the MCP inspector to debug the server. For uvx installations:
```bash
npx @modelcontextprotocol/inspector uvx mcp-server-time
```
Or if you've installed the package in a specific directory or are developing on it:
```bash
cd path/to/servers/src/time
npx @modelcontextprotocol/inspector uv run mcp-server-time
```
## Examples of Questions for Claude
1. "What time is it now?" (will use system timezone)
2. "What time is it in Tokyo?"
3. "When it's 4 PM in New York, what time is it in London?"
4. "Convert 9:30 AM Tokyo time to New York time"
## Contributing
We encourage contributions to help expand and improve mcp-server-time. Whether you want to add new time-related tools, enhance existing functionality, or improve documentation, your input is valuable.
For examples of other MCP servers and implementation patterns, see:
https://github.com/modelcontextprotocol/servers
Pull requests are welcome! Feel free to contribute new ideas, bug fixes, or enhancements to make mcp-server-time even more powerful and useful.
## License
mcp-server-time is licensed under the MIT License. This means you are free to use, modify, and distribute the software, subject to the terms and conditions of the MIT License. For more details, please see the LICENSE file in the project repository.

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[project]
name = "mcp-server-time"
version = "0.6.1"
description = "A Model Context Protocol server providing tools for time queries and timezone conversions for LLMs"
readme = "README.md"
requires-python = ">=3.10"
authors = [
{ name = "Mariusz 'maledorak' Korzekwa", email = "mariusz@korzekwa.dev" },
]
keywords = ["time", "timezone", "mcp", "llm"]
license = { text = "MIT" }
classifiers = [
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"License :: OSI Approved :: MIT License",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.10",
]
dependencies = [
"mcp>=1.0.0",
"pydantic>=2.0.0",
"tzdata>=2024.2",
]
[project.scripts]
mcp-server-time = "mcp_server_time:main"
[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[tool.uv]
dev-dependencies = [
"freezegun>=1.5.1",
"pyright>=1.1.389",
"pytest>=8.3.3",
"ruff>=0.8.1",
]

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