Document MCP Server

Document MCP Server

A simple MCP (Model Context Protocol) server and MCP client for managing documents using FastMCP.

Features

• Tools:

  • read_doc_contents: Read the contents of a document.
  • edit_document: Edit a document by replacing text.
  • return all the docs: List all document IDs.

• Resources:

  • docs://documents: JSON list of document IDs.
  • docs://documents/{doc_id}: Plain text content of a specific document.

• Prompts:

  • format_to_md: Prompt template for formatting documents to Markdown.

Prerequisites

• Python 3.12 or higher
• uv (Python package manager and project manager)

Installation

1. Ensure you have Python 3.12+ installed.

2. Install uv if not already installed:

   pip install uv
   

3. Clone or download this project to your local machine.

4. Navigate to the project directory:

   cd "path/to/mcp server"
   

5. Create a virtual environment and install dependencies:

   uv sync
   

Running the Server

To run the MCP server in development mode:

uv run mcp dev mcp_server.py

The server runs on stdio transport, suitable for MCP clients.

Testing the Functionality

Test client is provided in mcp_client.py to verify the server works.

To test:

1. In one terminal, start the server:

   uv run python mcp_server.py
   

2. In another terminal, run the test client:

   uv run mcp_client.py
   

This will connect to the server and list the available tools, printing them to the console.

For more advanced testing, you can modify mcp_client.py to call specific tools, read resources, or get prompts.

Example: To read a document content, you could add code like:

# Inside the async main function
doc_content = await client.call_tool("read_doc_contents", {"doc_id": "deposition.md"})
print(doc_content)

Project Structure

• mcp_server.py: The main MCP server implementation.
• mcp_client.py: A test client for interacting with the server.
• pyproject.toml: Project configuration and dependencies.

Notes

• The server uses an in-memory dictionary for documents. Changes are not persisted.
• Ensure the virtual environment is activated when running Python commands.