A comprehensive toolkit that enhances LLM capabilities through the Model Context Protocol, allowing LLMs to interact with external services including command-line operations, file management, Figma integration, and audio processing.
A unified context layer that connects your local data — repositories, documents, remote machines, and notes — to LLM interfaces through the Model Context Protocol (MCP).
A Model Context Protocol implementation that enables large language models to call external tools (like weather forecasts and GitHub information) through a structured protocol, with visualization of the model's reasoning process.
A lightweight framework for building and orchestrating AI agents through the Model Context Protocol, enabling users to create scalable multi-agent systems using only configuration files.
Define backends in natural language via Markdown files; provides auto-generated CRUD tools, custom actions, business rules, workflows, and system tools for LLMs through the Model Context Protocol.
