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Aider MCP Server - Experimental

@disler

リポジトリ

基本情報

カテゴリ

その他

トランスポート

stdio

作者

disler

Aider MCP Server - Experimental について

Minimal MCP Server for Aider

Aider MCP Server - Experimental の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "aider-mcp-server": {
      "command": "uv",
      "args": [
        "sync"
      ]
    }
  }
}

Aider MCP Server - Experimental のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is Aider MCP Server - Experimental?

A Model Context Protocol server that allows Claude Code to offload AI coding tasks to Aider, the open source AI coding assistant. It helps reduce costs, gives control over the coding model, and allows Claude Code to operate orchestratively by reviewing and revising code.

How to use Aider MCP Server - Experimental?

Clone the repository, run uv sync, configure API keys in .env, then add the server to Claud Code via claude mcp add with the appropriate --editor-model and --current-working-dir. Once running, use the aider_ai_code tool with a prompt and editable files, or list_models to discover available models.

Key features of Aider MCP Server - Experimental

  • Offloads AI coding tasks from Claude Code to Aider.
  • Uses the aider_ai_code tool with prompt and file paths.
  • Lists available models matching a substring via list_models.
  • Supports multiple AI model providers (OpenAI, Anthropic, Gemini, etc.).
  • Configurable editor model for separate coding and editing.
  • Operates over stdio transport with environment-based API keys.

Use cases of Aider MCP Server - Experimental

  • Refactoring a function in a Python file to handle exceptions.
  • Creating a new file based on natural language instructions.
  • Discovering which models are available for a given substring.
  • Using a cheaper or more capable model for editing than for initial coding.

よくある質問

1

What dependencies are required?

Python, uv, and API keys for the chosen AI model (set in `.env` or the `env` section of `mcpServers`).

2

How do I specify which model Aider should use?

Use the `--editor-model` argument when adding the server, and optionally the `model` parameter in `aider_ai_code` calls.

3

Where are my project files located during execution?

All file paths are relative to the `--current-working-dir` specified in the server configuration.

4

What transport does the server use?

It uses `stdio` transport, as defined in the `.mcp.json` configuration.

5

Can I test the server locally?

Yes, tests are run with `uv run pytest` and require a valid Gemini API key for AI coding tests.

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