Aider

An MCP server for offloading AI coding tasks to Aider, enhancing development efficiency and flexibility.

Model context protocol server for offloading AI coding work to Aider, enhancing development efficiency and flexibility.

This server allows Claude Code to offload AI coding tasks to Aider, the best open source AI coding assistant. By delegating certain coding tasks to Aider, we can reduce costs, gain control over our coding model and operate Claude Code in a more orchestrative way to review and revise code.

git clone https://github.com/disler/aider-mcp-server.git

- Configure your API keys in the.envfile (or use the mcpServers "env" section) to have the api key needed for the model you want to use in aider:

GEMINI_API_KEY=your_gemini_api_key_here OPENAI_API_KEY=your_openai_api_key_here ANTHROPIC_API_KEY=your_anthropic_api_key_here ...see .env.sample for more

- Copy and fill out the the.mcp.jsoninto the root of your project and update the--directoryto point to this project's root directory and the--current-working-dirto point to the root of your project.

{ "mcpServers": { "aider-mcp-server": { "type": "stdio", "command": "uv", "args": [ "--directory", "<path to this project>", "run", "aider-mcp-server", "--editor-model", "gpt-4o", "--current-working-dir", "<path to your project>" ], "env": { "GEMINI_API_KEY": "<your gemini api key>", "OPENAI_API_KEY": "<your openai api key>", "ANTHROPIC_API_KEY": "<your anthropic api key>", ...see .env.sample for more } } } }

# Test listing models uv run pytest src/aider_mcp_server/tests/atoms/tools/test_aider_list_models.py # Test AI coding uv run pytest src/aider_mcp_server/tests/atoms/tools/test_aider_ai_code.py

Note: The AI coding tests require a valid API key for the Gemini model. Make sure to set it in your.envfile before running the tests.

claude mcp add aider-mcp-server -s local \ -- \ uv --directory "<path to the aider mcp server project>" \ run aider-mcp-server \ --editor-model "gemini/gemini-2.5-pro-exp-03-25" \ --current-working-dir "<path to your project>"

claude mcp add aider-mcp-server -s local \ -- \ uv --directory "<path to the aider mcp server project>" \ run aider-mcp-server \ --editor-model "gemini/gemini-2.5-pro-preview-03-25" \ --current-working-dir "<path to your project>"

claude mcp add aider-mcp-server -s local \ -- \ uv --directory "<path to the aider mcp server project>" \ run aider-mcp-server \ --editor-model "openrouter/openrouter/quasar-alpha" \ --current-working-dir "<path to your project>"

claude mcp add aider-mcp-server -s local \ -- \ uv --directory "<path to the aider mcp server project>" \ run aider-mcp-server \ --editor-model "fireworks_ai/accounts/fireworks/models/llama4-maverick-instruct-basic" \ --current-working-dir "<path to your project>"

This MCP server provides the following functionalities:

- Takes a prompt and file paths
- Uses Aider to implement the requested changes
- Returns success or failure

- Provides a list of models matching a substring
- Useful for discovering supported models

This MCP server exposes the following tools:

This tool allows you to run Aider to perform AI coding tasks based on a provided prompt and specified files.

- ai_coding_prompt(string, required): The natural language instruction for the AI coding task.
- relative_editable_files(list of strings, required): A list of file paths (relative to thecurrent_working_dir) that Aider is allowed to modify. If a file doesn't exist, it will be created.
- relative_readonly_files(list of strings, optional): A list of file paths (relative to thecurrent_working_dir) that Aider can read for context but cannot modify. Defaults to an empty list[].
- model(string, optional): The primary AI model Aider should use for generating code. Defaults to"gemini/gemini-2.5-pro-exp-03-25". You can use thelist_modelstool to find other available models.
- editor_model(string, optional): The AI model Aider should use for editing/refining code, particularly when using architect mode. If not provided, the primarymodelmight be used depending on Aider's internal logic. Defaults toNone.

Use the Aider AI Code tool to: Refactor the calculate_sum function in calculator.py to handle potential TypeError exceptions.

{ "name": "aider_ai_code", "parameters": { "ai_coding_prompt": "Refactor the calculate_sum function in calculator.py to handle potential TypeError exceptions.", "relative_editable_files": ["src/calculator.py"], "relative_readonly_files": ["docs/requirements.txt"], "model": "openai/gpt-4o" } }

- A simple dict: {success, diff}

- success: boolean - Whether the operation was successful.
- diff: string - The diff of the changes made to the file.

This tool lists available AI models supported by Aider that match a given substring.

- substring(string, required): The substring to search for within the names of available models.

Use the Aider List Models tool to: List models that contain the substring "gemini".

{ "name": "list_models", "parameters": { "substring": "gemini" } }

- A list of model name strings that match the provided substring. Example:["gemini/gemini-1.5-flash", "gemini/gemini-1.5-pro", "gemini/gemini-pro"]

- Server layer: Handles MCP protocol communication
- Atoms layer: Individual, pure functional components

- Tools: Specific capabilities (AI coding, listing models)
- Utils: Constants and helper functions
- Data Types: Type definitions using Pydantic

All components are thoroughly tested for reliability.

The project is organized into the following main directories and files:

. ├── ai_docs # Documentation related to AI models and examples │ ├── just-prompt-example-mcp-server.xml │ └── programmable-aider-documentation.md ├── pyproject.toml # Project metadata and dependencies ├── README.md # This file ├── specs # Specification documents │ └── init-aider-mcp-exp.md ├── src # Source code directory │ └── aider_mcp_server # Main package for the server │ ├── __init__.py # Package initializer │ ├── __main__.py # Main entry point for the server executable │ ├── atoms # Core, reusable components (pure functions) │ │ ├── __init__.py │ │ ├── data_types.py # Pydantic models for data structures │ │ ├── logging.py # Custom logging setup │ │ ├── tools # Individual tool implementations │ │ │ ├── __init__.py │ │ │ ├── aider_ai_code.py # Logic for the aider_ai_code tool │ │ │ └── aider_list_models.py # Logic for the list_models tool │ │ └── utils.py # Utility functions and constants (like default models) │ ├── server.py # MCP server logic, tool registration, request handling │ └── tests # Unit and integration tests │ ├── __init__.py │ └── atoms # Tests for the atoms layer │ ├── __init__.py │ ├── test_logging.py # Tests for logging │ └── tools # Tests for the tools │ ├── __init__.py │ ├── test_aider_ai_code.py # Tests for AI coding tool │ └── test_aider_list_models.py # Tests for model listing tool

- src/aider_mcp_server: Contains the main application code.

- atoms: Holds the fundamental building blocks. These are designed to be pure functions or simple classes with minimal dependencies.

- tools: Each file here implements the core logic for a specific MCP tool (aider_ai_code,list_models).
- utils.py: Contains shared constants like default model names.
- data_types.py: Defines Pydantic models for request/response structures, ensuring data validation.
- logging.py: Sets up a consistent logging format for console and file output.

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