What is Aider Make Mcp

Aider-make-mcp is an MCP server designed for processing document, code, and data contexts, following the official Model Context Protocol (MCP) v1.0 specification.

Use cases

Use cases include integrating with applications that require citation support for documents, handling code snippets in specific programming languages, and processing structured data for analytics.

How to use

To use aider-make-mcp, install the required dependencies using ‘pip install fastapi uvicorn’, then run the server with ‘python mcp_server.py’. Configure your client application to connect to the server by specifying the command, arguments, and environment variables.

Key features

Key features include document context processing with citation support, language-specific code context processing, structured data context processing, health check endpoint, error handling, and support for context-specific options.

Where to use

Aider-make-mcp can be used in various fields such as software development, data analysis, and document management where context-aware processing of documents, code, and data is required.

Model Context Protocol (MCP) Server

An implementation of Anthropic’s Model Context Protocol following the official specification from https://modelcontextprotocol.io

This server implements the MCP v1.0 specification and provides:

Core Features

• Document context processing with citation support
• Code context processing with language-specific handling
• Data context processing with structured results
• Health check endpoint with capabilities reporting
• Error handling and validation
• Support for context-specific options

Features

• REST API implementation of MCP
• Support for text, code, and data context types
• Proper error handling and metadata support
• FastAPI-based server
• Aligned with official MCP specification

Requirements

• Python 3.8+
• FastAPI
• Uvicorn

Installation

pip install fastapi uvicorn

Running the Server

python mcp_server.py

Client Configuration

To configure this MCP server in your client application, add the following to your configuration:

{
  "mcpServers": {
    "mcp_server": {
      "command": "python",
      "args": [
        "mcp_server.py"
      ],
      "env": {
        "MCP_PORT": "8000",
        "MCP_HOST": "0.0.0.0"
      }
    }
  }
}

Key Configuration Options:

• command: The Python interpreter command
• args: Arguments to pass to the command
  • Server filename (e.g., “mcp_server.py”)
• env: Environment variables for server configuration
  • MCP_PORT: Port to run the server on (default: 8000)
  • MCP_HOST: Host to bind the server to (default: 0.0.0.0)

Claude Desktop Integration Guide

Prerequisites

1. Claude Desktop app installed (version 1.2.0 or later)
2. Python 3.8+ installed
3. MCP server running locally
4. Proper client configuration as shown above

Step-by-Step Setup

1. Install Dependencies

   pip install -r requirements.txt
   

2. Start the MCP Server

   python mcp_server.py
   

   The server will start on http://localhost:8000

3. Configure Claude Desktop

   • Open Claude Desktop app
   • Go to Settings > Integrations > MCP Servers
   • Click “Add New Server”
   • Enter the following details:
     • Name: Local MCP Server
     • URL: http://localhost:8000
     • Description: Local MCP server for testing
   • Click “Save”

4. Test the Connection

   • In the MCP Servers list, click the “Test Connection” button next to your server
   • You should see a green checkmark if the connection is successful

5. Using MCP in Conversations

   • Start a new conversation in Claude Desktop
   • Use the @mcp prefix to route queries to your MCP server
   • Example queries:

     @mcp Analyze this code snippet: [your code here]
     @mcp What can you tell me about this document?
     @mcp Process this data: [your data here]
     

Troubleshooting

• Connection Failed: Ensure the MCP server is running and accessible
• Timeout Errors: Check your network settings and firewall rules
• Invalid Responses: Verify the server logs for any errors

Example Conversation Flow

User: @mcp What can you tell me about this code?
def factorial(n):
    if n == 0:
        return 1
    return n * factorial(n-1)

Claude: [MCP Response] Processed code query: This appears to be a recursive implementation of the factorial function...

API Endpoints

• POST /context
  • Request:

    {
      "query": "your query",
      "context_type": "text|code|data",
      "context": {},
      "metadata": {}
    }
    

  • Response:

    {
      "response": "Processed response",
      "context_type": "text|code|data",
      "metadata": {},
      "error": null
    }
    

Future Plans

• Add authentication and security
• Implement data source integrations
• Add support for streaming responses
• Implement context caching
• Add support for context versioning