aider-mcp-server

Aider MCP Server

A Machine Cognition Protocol (MCP) server that provides AI coding capabilities using Aider.

Table of Contents

• Overview
• Features
• Prerequisites
• Installation
• Configuration
• Running the Server
• MCP Tools
• Integration with MCP Clients
• Troubleshooting
• License

Overview

This MCP server leverages Aider, a powerful AI coding assistant, to provide coding capabilities via a standardized API. By discretely offloading work to Aider, we can reduce costs while using model-specific capabilities to create more reliable code through multiple focused LLM calls.

Features

• AI Code Generation: Run one-shot coding tasks with Aider to add, fix, or enhance code
• Model Selection: Query available models to choose the most appropriate one for your task
• Flexible Configuration: Configure Aider sessions with customizable settings
• Multi-transport Support: Run via Server-Sent Events (SSE) or stdio for flexible integration
• General Question Answering: Ask an LLM questions using a simple prompt

Prerequisites

• Python: 3.10 or higher
• Package Manager: uv (recommended) or pip
• API Keys: Depending on the models you want to use, you'll need API keys for:
  • OpenAI (for GPT models)
  • Anthropic (for Claude models)
  • Google (for Gemini models)

Installation

1. Clone the repository:

   git clone https://github.com/your-username/aider-mcp.git
   cd aider-mcp
   

2. Install the package:

   uv sync
   uv venv
   uv pip install -e .
   

3. Run the tests to ensure everything is working:

   uv run pytest
   

Configuration

Configure the server behavior using environment variables in a .env file:

# Create environment file from example
cp .env.example .env

Edit the .env file to configure transport, host, port, and API keys.

*Required only if using models from that provider

Command Line Options

• --editor-model: Model to use for editing (default: gemini/gemini-2.5-pro-exp-03-25)
• --architect-model: Model to use for architecture planning (optional)
• --cwd: Current working directory (default: current directory)

Running the Server

Start the Server (SSE Mode)

# Using the module directly
uv run python -m aider_mcp_server

Or with custom settings:

uv run python -m aider_mcp_server --editor-model "gemini/gemini-2.5-pro-exp-03-25" --cwd "/path/to/project"

You should see output similar to:

Starting server with transport: sse
Using SSE transport on 0.0.0.0:8050

Using stdio Mode

When using stdio mode, you don't need to start the server separately - the MCP client will start it automatically when configured properly (see Integration with MCP Clients).

MCP Tools

The Aider MCP server exposes the following tools:

ai_code

Run Aider to perform coding tasks.

Parameters:

• ai_coding_prompt: The prompt for the AI coding task
• relative_editable_files: List of files that can be edited
• relative_readonly_files: (Optional) List of files that should be read-only
• settings: (Optional) Settings for the Aider session

Example:

{
  "ai_coding_prompt": "Add a function that calculates the factorial of a number",
  "relative_editable_files": ["math.py"],
  "settings": {
    "auto_commits": false,
    "use_git": false
  }
}

get_models

List available Aider models filtered by substring.

Parameters:

• substring: Substring to filter models by

Example:

{
  "substring": "openai"
}

ask_question

Send a prompt to an LLM and return the response.

Parameters:

• prompt: The question or statement to send
• model: (Optional) The LLM model to use

Example:

{
  "prompt": "What is the capital of France?",
  "model": "gpt-4o"
}

Integration with MCP Clients

Configure your MCP client to connect to the SSE endpoint:

{
  "mcpServers": {
    "aider-mcp-server": {
      "transport": "sse",
      "serverUrl": "http://localhost:8050/sse"
    }
  }
}

Stdio Integration

Configure your MCP client to run the server via stdio:

{
  "mcpServers": {
    "aider-mcp-server": {
      "transport": "stdio",
      "command": "python",
      "args": ["-m", "aider_mcp_server"],
      "env": {
        "TRANSPORT": "stdio"
      }
    }
  }
}

Integration with MCP Clients

Using Docker

{
    "mcpServers": {
      "aider-mcp-server": {
        "command": "docker",
        "args": [ "run", "-i", "--rm",
          "--mount", "type=bind,source=<YOUR_FULL_PATH>",
          "-e", "TRANSPORT=stdio",
          "-e", "EDITOR_MODEL=gemini/gemini-2.5-pro-preview-03-25",
          "-e", "GEMINI_API_KEY=<YOUR_API_KEY>",
          "danielscholl/aider-mcp-server"
        ]
      }
    }
  }