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Maintenance of a set of tools to enhance LLM through MCP protocols.

Project description

mcp-toolbox

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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.

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.

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

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

Claude Desktop Configuration

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

{
  "mcpServers": {
    "zerolab-toolbox": {
      "command": "uvx",
      "args": ["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"
      }
    }
  }
}

You can generate a debug configuration template using:

uv run generate_config_template.py

Available Tools

Command Line Tools

Tool Description
execute_command Execute a command line instruction

File Operations Tools

Tool Description
read_file_content Read content from a file
write_file_content Write content to a file
replace_in_file Replace content in a file using regular expressions
list_directory List directory contents with detailed information

Figma Tools

Tool Description
figma_get_file Get a Figma file by key
figma_get_file_nodes Get specific nodes from a Figma file
figma_get_image Get images for nodes in a Figma file
figma_get_image_fills Get URLs for images used in a Figma file
figma_get_comments Get comments on a Figma file
figma_post_comment Post a comment on a Figma file
figma_delete_comment Delete a comment from a Figma file
figma_get_team_projects Get projects for a team
figma_get_project_files Get files for a project
figma_get_team_components Get components for a team
figma_get_file_components Get components from a file
figma_get_component Get a component by key
figma_get_team_component_sets Get component sets for a team
figma_get_team_styles Get styles for a team
figma_get_file_styles Get styles from a file
figma_get_style Get a style by key

XiaoyuZhouFM Tools

Tool Description
xiaoyuzhoufm_download Download a podcast episode from XiaoyuZhouFM with optional automatic m4a to mp3 conversion

Audio Tools

Tool Description
get_audio_length Get the length of an audio file in seconds
get_audio_text Get transcribed text from a specific time range in an audio file

Markitdown Tools

Tool Description
convert_file_to_markdown Convert any file to Markdown using MarkItDown
convert_to_markdown Convert text to Markdown using MarkItDown

Web Tools

Tool Description
get_html Get HTML content from a URL
save_html Save HTML from a URL to a file
search_with_tavily Search the web using Tavily (requires API key)
search_with_duckduckgo Search the web using DuckDuckGo (requires API key)

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:
  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 text to Markdown:
    • "Convert this file to Markdown: document.docx"
    • "Convert this HTML to Markdown:

      Hello World

      "
  8. Ask Claude to work with web content:

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.

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