mcp_server_for_claudes_toolbox
Exposes a set of CLI tools (test generation, documentation generation, linting, test running, code search) to AI assistants via MCP, allowing them to perform these tasks through natural language.
README
mcp_server_for_claudes_toolbox
Author: Claude 3.7 Sonnet, Kyle Rose
Version: 0.2.0
A server application that exposes Claude's Toolbox utility programs via the Model Context Protocol (MCP), making them accessible to AI assistants like Claude through different interfaces (Claude Code, Claude Desktop, Copilot, etc.).
Features
- Arbitrary function registration and invocation. Just add a function to the
tools/functionsfolder, name the file after it, and it will be available for use. - Exposes a set of standalone command-line interface (CLI) tools for various tasks. Current CLI tools include:
- test_generator: Creates unittest test files from JSON specifications.
- documentation_generator: Generates markdown documentation from Python source code.
- lint_a_python_codebase: Fixes common linting issues in Python files like blank lines, trailing spaces, and newlines.
- run_tests_and_save_their_results: Runs unit tests, type checking, and linting for Python projects, and saves the results as JSON and Markdown files.
- codebase_search: Searches code with pattern matching.
- Each CLI tool is a complete program unto itself and can be set up to use its own virtual environments. The server will automatically activate the appropriate virtual environment for each tool when called.
- Customizable server settings in
configs.yamlfile, allowing for easy changes settings like verbosity, log level, host, port, and reload options. - Cross-platform tool support for WSL2, Linux/MacOS, and Windows. This allows the server to register and run tools written for a Posix environment on Windows, and vice versa. Just add the appropriate config code to the MCP config file for your platform.
Configuration
The server can be configured through the configs.yaml file:
verbose: True
log_level: 10
host: '0.0.0.0'
port: 8000
reload: True
load_from_paths_csv: True
Requirements
- WSL2, Linux. Window support is forthcoming.
- Python 3.12+
- mcp # for MCP server
- aiofile # for async file operations
- anthropic # for LLM API access from Anthropic
- coverage # for test coverage
- duckdb # for cross-platform database operations
- flask # for web framework
- flake8 # for linting
- httpx # for async HTTP requests
- jinja2 # for templating
- mcp # for Claude tool server API
- multiformats # for CID creation
- mypy # for type checking
- numpy # for numerical operations
- openai # for LLM api access from OpenAI
- psutil # for system and process utilities
- pydantic # for data validation and settings management
- pytest # for testing
- pyyaml # for YAML parsing
- tqdm # for progress bars
Installation
- Clone this repository:
git clone https://github.com/the-ride-never-ends/claudes_toolbox
- Run the installation script:
For Linux/MacOS:
cd claudes_toolbox
bash ./install_server.sh
For Windows:
cd claudes_toolbox
cmd .\install_server.bat
- Copy-paste the respective config code into the relevant MCP config file.
For Claude Desktop for Windows, this is typically located at
C:\Users\<username>\AppData\Roaming\Claude\claude_desktop_config.json.
Server hosted on WSL:
run_wsl.config
"claudes-toolbox": {
"command": "wsl",
"args": [
"bash",
"-c",
"source ~/.bashrc && ~/claudes_toolbox/mcp_server_for_claudes_toolbox/start_claudes_toolbox_server.sh --called-with-wsl"
]
}
Server hosted on Linux/MacOS:
run_linux.config
"claudes-toolbox": {
"command": "bash",
"args": [
"-c",
"source ~/.bashrc || source ~/.bash_profile || source ~/.zshrc; ~/claudes_toolbox/start_server.sh"
]
}
Server hosted on Windows:
"claudes-toolbox": {
"command": "cmd.exe",
"args": [
"/c",
"C:\\path\\to\\start_server.bat"
]
}
- Git-clone the other repositories into the
claude_toolbox/tools/clidirectory:
cd claudes_toolbox/tools
git clone https://github.com/the-ride-never-ends/documentation_generator
git clone https://github.com/the-ride-never-ends/test_generator
git clone https://github.com/the-ride-never-ends/run_tests_and_save_their_results
git clone https://github.com/the-ride-never-ends/lint_a_python_codebase
git clone https://github.com/the-ride-never-ends/codebase_search
The server will automatically activate the appropriate virtual environment for each tool when called.
Usage
Integrated applications like Copilot, Claude Code, and Claude Desktop can call the server using the MCP protocol. The server starts automatically when the given command is executed.
The server works by:
- Running tools through subprocess calls to the command line
- Using a wrapper function that activates virtual environments
- Exposing each tool with appropriate parameters via the MCP protocol
Directory Structure
mcp_server_for_claudes_toolbox/
├── docs/ # Documentation files
├── tests/ # Test files and test cases
├── utils/ # Utility scripts
├── data/ # Data files used by the program (if any)
├── app.py # MCP server application
├── configs.py # Configurations singleton for the program
├── logger.py # Logger singleton for the program
├── TODO.md # Todo list
├── CHANGELOG.md # Changelog list
├── claude.md # Instructions to Claude in Claude Code API
├── requirements.txt # 3rd-party library requirements
├── install.sh # Set-up venv and install requirements
├── start.sh # Script to start the server
└── README.md # This file
License
MIT
推荐服务器
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。
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。
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。
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。
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。
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。
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。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
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。