mcp-toolbox

mcp-toolbox

A comprehensive toolkit for enhancing LLM capabilities through the Model Context Protocol (MCP). This package provides a collection of tools that allow LLMs to interact with external services and APIs, extending their functionality beyond text generation.

• GitHub repository: https://github.com/ai-zerolab/mcp-toolbox/
• (WIP)Documentation: https://ai-zerolab.github.io/mcp-toolbox/

Features

*nix is our main target, but Windows should work too.

• Command Line Execution: Execute any command line instruction through LLM
• Figma Integration: Access Figma files, components, styles, and more
• Extensible Architecture: Easily add new API integrations
• MCP Protocol Support: Compatible with Claude Desktop and other MCP-enabled LLMs
• Comprehensive Testing: Well-tested codebase with high test coverage

Installation

Using uv (Recommended)

We recommend using uv to manage your environment.

# Install uv
curl -LsSf https://astral.sh/uv/install.sh | sh  # For macOS/Linux
# or
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"  # For Windows

Then you can use uvx "mcp-toolbox@latest" stdio as commands for running the MCP server for latest version. Audio and memory tools are not included in the default installation., you can include them by installing the all extra:

[audio] for audio tools, [memory] for memory tools, [all] for all tools

uvx "mcp-toolbox[all]@latest" stdio

Installing via Smithery

To install Toolbox for LLM Enhancement for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @ai-zerolab/mcp-toolbox --client claude

Using pip

pip install "mcp-toolbox[all]"

And you can use mcp-toolbox stdio as commands for running the MCP server.

Configuration

Environment Variables

The following environment variables can be configured:

• FIGMA_API_KEY: API key for Figma integration
• TAVILY_API_KEY: API key for Tavily integration
• DUCKDUCKGO_API_KEY: API key for DuckDuckGo integration
• BFL_API_KEY: API key for Flux image generation API

Memory Storage

Memory tools store data in the following locations:

• macOS: ~/Documents/zerolab/mcp-toolbox/memory (syncs across devices via iCloud)
• Other platforms: ~/.zerolab/mcp-toolbox/memory

Full Configuration

To use mcp-toolbox with Claude Desktop/Cline/Cursor/..., add the following to your configuration file:

{
  "mcpServers": {
    "zerolab-toolbox": {
      "command": "uvx",
      "args": ["--prerelease=allow", "mcp-toolbox@latest", "stdio"],
      "env": {
        "FIGMA_API_KEY": "your-figma-api-key",
        "TAVILY_API_KEY": "your-tavily-api-key",
        "DUCKDUCKGO_API_KEY": "your-duckduckgo-api-key",
        "BFL_API_KEY": "your-bfl-api-key"
      }
    }
  }
}

For full features:

{
  "mcpServers": {
    "zerolab-toolbox": {
      "command": "uvx",
      "args": [
        "--prerelease=allow",
        "--python=3.12",
        "mcp-toolbox[all]@latest",
        "stdio"
      ],
      "env": {
        "FIGMA_API_KEY": "your-figma-api-key",
        "TAVILY_API_KEY": "your-tavily-api-key",
        "DUCKDUCKGO_API_KEY": "your-duckduckgo-api-key",
        "BFL_API_KEY": "your-bfl-api-key"
      }
    }
  }
}

You can generate a debug configuration template using:

uv run generate_config_template.py

Available Tools

Command Line Tools

File Operations Tools

Figma Tools

XiaoyuZhouFM Tools

Audio Tools

Memory Tools

Markitdown Tools

Web Tools

Flux Image Generation Tools

Usage Examples

Running the MCP Server

# Run with stdio transport (default)
mcp-toolbox stdio

# Run with SSE transport
mcp-toolbox sse --host localhost --port 9871

Using with Claude Desktop

1. Configure Claude Desktop as shown in the Configuration section
2. Start Claude Desktop
3. Ask Claude to interact with Figma files:
   • "Can you get information about this Figma file: 12345abcde?"
   • "Show me the components in this Figma file: 12345abcde"
   • "Get the comments from this Figma file: 12345abcde"
4. Ask Claude to execute command line instructions:
   • "What files are in the current directory?"
   • "What's the current system time?"
   • "Show me the contents of a specific file."
5. Ask Claude to download podcasts from XiaoyuZhouFM:
   • "Download this podcast episode: https://www.xiaoyuzhoufm.com/episode/67c3d80fb0167b8db9e3ec0f"
   • "Download and convert to MP3 this podcast: https://www.xiaoyuzhoufm.com/episode/67c3d80fb0167b8db9e3ec0f"
6. Ask Claude to work with audio files:
   • "What's the length of this audio file: audio.m4a?"
   • "Transcribe the audio from 60 to 90 seconds in audio.m4a"
   • "Get the text from 2:30 to 3:00 in the audio file"
7. Ask Claude to convert files or URLs to Markdown:
   • "Convert this file to Markdown: document.docx"
   • "Convert this webpage to Markdown: https://example.com"
8. Ask Claude to work with web content:
   • "Get the HTML content from https://example.com"
   • "Save the HTML from https://example.com to a file"
   • "Search the web for 'artificial intelligence news'"
9. Ask Claude to generate images with Flux:
   • "Generate an image of a beautiful sunset over mountains"
   • "Create an image of a futuristic city and save it to my desktop"
   • "Generate a portrait of a cat in a space suit"
10. Ask Claude to use memory tools:
    • "Remember this important fact: The capital of France is Paris"
    • "What's my current session ID?"
    • "Recall any information about France"
    • "Think about the implications of climate change"
    • "Forget all stored memories"

Development

Local Setup

Fork the repository and clone it to your local machine.

# Install in development mode
make install
# Activate a virtual environment
source .venv/bin/activate  # For macOS/Linux
# or
.venv\Scripts\activate  # For Windows

Running Tests

make test

Running Checks

make check

Building Documentation

make docs

Adding New Tools

To add a new API integration:

1. Update config.py with any required API keys
2. Create a new module in mcp_toolbox/
3. Implement your API client and tools
4. Add tests for your new functionality
5. Update the README.md with new environment variables and tools

See the development guide for more detailed instructions.

Contributing

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

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

License

This project is licensed under the terms of the license included in the repository.