Maintenance of a set of tools to enhance LLM through MCP protocols.
Until 2026-09-24 this record combined several servers published from one repository. The others now have records of their own: mcp-toolbox. Checks from before that date include them.
Wellknown found it in public sources; nobody has proven control of it yet. Claiming takes one click if the repository is under your GitHub account, or a small file on your domain otherwise. Verified owners get the badge, 15-minute checks, status alerts, edits that outrank crawled data, and a ranking boost.
Agents can do it too: POST https://wellknown.network/api/v1/claims with {"agent":"iflow-mcp-ai-zerolab-mcp-toolbox","method":"well_known_file"} — machine-readable steps at claim.json, guide at /docs/claim.
Everything here was measured by our prober or read from a registry. Nothing is self-reported.
Attributed to the source that supplied each field. Treated as claims, not facts.
# mcp-toolbox [](https://img.shields.io/github/v/release/ai-zerolab/mcp-toolbox) [](https://github.com/ai-zerolab/mcp-toolbox/actions/workflows/main.yml?query=branch%3Amain) [](https://codecov.io/gh/ai-zerolab/mcp-toolbox) [](https://img.shields.io/github/commit-activity/m/ai-zerolab/mcp-toolbox) [](https://img.shields.io/github/license/ai-zerolab/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](https://github.com/astral-sh/uv) to manage your environment. ```bash # 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-…
Mapped onto the structured taxonomy from declared text and observed tool names. Confidence shown for derived entries.
Every source is kept verbatim. Field changes are logged as events.