codemenu-mcp

codemenu-mcp

Enables AI assistants to search and retrieve code snippets from the CodeMenu snippet manager via the local HTTP API.

Category
访问服务器

README

codemenu-mcp

MCP server for CodeMenu snippet manager.

Overview

This is a Model Context Protocol (MCP) server that provides integration with the CodeMenu local HTTP API, allowing AI assistants to access and search through code snippets stored in CodeMenu.

Features

The server exposes the following tools for interacting with CodeMenu:

  • list_snippets - List snippets without full code content (to reduce token usage). Returns id, title, description, language, abbreviation, tags, and group info. Supports filtering by query, language, tag, or group.
  • get_snippet - Retrieve the full details of a specific snippet by ID, including complete code content
  • list_tags - List all available tags in CodeMenu
  • list_groups - List all available groups in CodeMenu

Prerequisites

  • CodeMenu must be running on your Mac (Learn more)
  • API must be enabled in CodeMenu settings (CodeMenu → Settings → API)
  • Node.js >= 18.0.0

CodeMenu API Setup

  1. Open CodeMenu
  2. Go to Settings → API
  3. Enable the API server
  4. Note the port (default: 1300)
  5. Optionally, set an API key for authentication

The CodeMenu API runs locally at http://127.0.0.1:1300/v1 by default.

Installation

From npm (when published)

npm install -g git+https://github.com/Extiri/codemenu-mcp.git

From source

git clone https://github.com/Extiri/codemenu-mcp.git
cd codemenu-mcp
npm install
npm link

Configuration

The server connects to the local CodeMenu API and supports the following environment variables:

Environment Variables

  • CODEMENU_API_URL - The base URL for the CodeMenu API (default: http://127.0.0.1:1300/v1)
  • CODEMENU_API_KEY - Your CodeMenu API key

Example Configuration for Claude Desktop

Add this to your Claude Desktop configuration file:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

Windows: %APPDATA%/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "codemenu": {
      "command": "node",
      "args": ["/path/to/codemenu-mcp/index.js"],
      "env": {
        "CODEMENU_API_URL": "http://127.0.0.1:1300/v1",
        "CODEMENU_API_KEY": "your-api-key"
      }
    }
  }
}

Or if installed globally via npm:

{
  "mcpServers": {
    "codemenu": {
      "command": "codemenu-mcp",
      "env": {
        "CODEMENU_API_KEY": "your-api-key"
      }
    }
  }
}

Note: If you didn't enable API key protection in CodeMenu settings, you can omit the CODEMENU_API_KEY environment variable.

Usage

Once configured, the server will be automatically started by your MCP client (e.g., Claude Desktop). The AI assistant will have access to your CodeMenu snippets and can:

  • Browse and search through your code snippets
  • Find snippets by language, tags, or groups
  • Retrieve specific snippets with full code content when needed
  • List available tags and groups for better organization

Example Interactions

Searching snippets:

"Search my CodeMenu snippets for sorting algorithms"

Listing snippets by language:

"Show me all my JavaScript snippets from CodeMenu"

Getting a specific snippet:

"Show me the full code for snippet ID ABC123"

Listing tags:

"What tags do I have in CodeMenu?"

Development

Running the Server

npm start

The server communicates over stdio, which is the standard transport for MCP servers.

Testing

npm test

This validates that the server correctly implements the MCP protocol. To test actual API calls, make sure CodeMenu is running with the API enabled.

Project Structure

  • index.js - Main server implementation
  • package.json - Project metadata and dependencies
  • test.js - MCP protocol test suite
  • README.md - This file
  • LICENSE - MIT license
  • .gitignore - Files to exclude from git

API Reference

The server implements the Model Context Protocol and exposes tools that correspond to CodeMenu API endpoints:

  • GET /snippets - List snippets with optional filters (query, language, tag, group)
  • GET /tags - List all tags
  • GET /groups - List all groups

For detailed information about the CodeMenu API, refer to the CodeMenu API documentation.

Requirements

  • Node.js >= 18.0.0
  • CodeMenu application with API enabled
  • MCP client (e.g., Claude Desktop)

License

MIT

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Support

For issues related to:

Troubleshooting

Server can't connect to CodeMenu:

  • Ensure CodeMenu application is running
  • Check that API is enabled in CodeMenu settings
  • Verify the port matches your configuration (default: 1300)
  • If you enabled API key protection, ensure CODEMENU_API_KEY is set correctly

No snippets returned:

  • Verify you have snippets in CodeMenu
  • Check that your search filters aren't too restrictive
  • Try listing without filters first

Authentication errors:

  • Check if the CODEMENU_API_KEY environment variable is set properly

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选