Aider MCP Server - Experimental

@disler

代码仓库

基本信息

分类

其他

传输方式

stdio

作者

disler

关于 Aider MCP Server - Experimental

Minimal MCP Server for Aider

Aider MCP Server - Experimental 配置

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": {
      "command": "uv",
      "args": [
        "sync"
      ]
    }
  }
}

Aider MCP Server - Experimental 工具

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。

概览

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.

常见问题

What dependencies are required?

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

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.

Where are my project files located during execution?

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

What transport does the server use?

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

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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