What tools does the server expose?
The server exposes `ai_code` for performing coding tasks and `get_models` for listing available Aider models filtered by a substring.
@danielscholl
基本信息
An experimental MCP server to use aider as a coding agent.
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"aider-mcp-server-danielscholl": {
"command": "uv",
"args": [
"venv"
]
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
A Machine Cognition Protocol (MCP) server that provides AI coding capabilities using Aider. It leverages Aider, a powerful AI coding assistant, to offer coding via a standardized API, reducing costs by discretely offloading work to Aider while using model-specific capabilities for more reliable code through multiple focused LLM calls.
Install by cloning the repository and running uv pip install -e . in a virtual environment. Configure the server via a .env file (setting transport, host, port, and API keys) or CLI options (--editor-model, --architect-model, --cwd). Start in SSE mode with uv run python -m aider_mcp_server, or configure an MCP client to run it automatically via stdio or Docker.
The server exposes `ai_code` for performing coding tasks and `get_models` for listing available Aider models filtered by a substring.
The server supports both Server-Sent Events (SSE) and stdio transport modes.
Python 3.10 or higher is required. The recommended package manager is uv, though pip can also be used.
API keys from OpenAI, Anthropic, or Google (Gemini) are required depending on which models you intend to use. Each key is configured via environment variables (`OPENAI_API_KEY`, `ANTHROPIC_API_KEY`, `GEMINI_API_KEY`).
Set the `TRANSPORT` environment variable (default `sse`), and optionally `HOST` (default `0.0.0.0`) and `PORT` (default `8050`) for SSE mode. The editor model can be set via `--editor-model` (default `gemini/gemini-2.5-pro-exp-03-25`).
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