Simple MCP Tool Server

A simple MCP server that exposes a website fetching tool using SSE transport.

Requirements

• Python 3.10 or higher (tested on Python 3.13)

Installation

# Create a virtual environment
python3 -m venv venv

# Activate the virtual environment
source venv/bin/activate

# Install the package and dependencies
pip install -r requirements.txt

MCP Python SDK Documentation

The MCP Python SDK documentation has been split into smaller files and organized in the mcp_python_sdk_docs/ directory. This structure makes it easier for AI agents to navigate and understand the SDK. The documentation covers:

• Core concepts (servers, resources, tools, etc.)
• Running MCP servers in different modes
• Examples and advanced usage
• And more!

Check out the index file for the complete table of contents.

Usage

The package provides a command-line interface (CLI) with several commands to manage the MCP server:

Starting the server

Start the server on the default port (7000) or specify a custom port:

# Using default port (7000)
python -m mcp_simple_tool start

# Using custom port
python -m mcp_simple_tool start --port 8000

Managing the server

# Check if server is running
python -m mcp_simple_tool check [--port PORT]

# Stop the server
python -m mcp_simple_tool stop [--port PORT]

# Restart the server (stop and start)
python -m mcp_simple_tool restart [--port PORT]

The restart command will:

1. Stop any existing server on the specified port
2. Start a new server in the background
3. Wait until the server is responsive
4. Log output to server.log

CLI quick reference

Command	Purpose
start	Start the server
stop	Stop the server
check	Health-check
restart	Stop & start
call	Invoke a tool locally or against a running server

Server Tools

The server exposes the following tools:

• fetch: Fetches a website and returns its content

  • url: The URL of the website to fetch (required)

• search_docs: Semantic search across SDK documentation files

  • query: Search phrase or question (required)
  • k: Number of top matches to return (optional, default = 3)

Testing a tool

You can test the tools using the CLI:

# Test the fetch tool
python -m mcp_simple_tool call --tool fetch --args '{"url":"https://awesome-testing.com"}'

# Test the search_docs tool
python -m mcp_simple_tool call --tool search_docs --args '{"query":"Context object"}'

Development Setup

For development, install additional tools:

pip install -e .
pip install -r requirements.txt

Use the Makefile for common tasks:

# Format code
make fmt

# Run linters
make lint

# Run tests
make test

The test suite has a built-in 20-second timeout for all tests to prevent hanging, especially with SSE endpoints. For individual tests, a more strict timeout can be specified using the @pytest.mark.timeout(seconds) decorator.

Semantic Search Index

For the search_docs tool, you can manually build or rebuild the vector index:

# Build or rebuild the semantic search index
python scripts/build_doc_index.py

The index is built automatically on first tool use if it doesn't exist.

Project Architecture

mcp_simple_tool/
    __init__.py          # Package initialization
    __main__.py          # Entry point when run as module
    cli.py               # Command-line interface
    server/              # Server implementation
        __init__.py      # Server package initialization
        app.py           # ASGI application setup
        config.py        # Configuration settings
        handlers.py      # Tool implementations
        http.py          # HTTP utilities
    semantic_search/     # Semantic search functionality
        __init__.py      # Package initialization
        indexing.py      # Build and persist vector store
        search.py        # Load index and query helpers

Using with Cursor

This MCP server can be used with Cursor as a client. For setup:

1. Run the server in a terminal:

source venv/bin/activate
python -m mcp_simple_tool start
# or use the restart command
python -m mcp_simple_tool restart

2. Configure Cursor by creating a .cursor/mcp.json file:

{
  "mcpServers": {
    "website-fetcher-sse": {
      "url": "http://localhost:7000/sse"
    }
  }
}

3. Mention the server in your prompts when using Cursor