microsoft/markitdown
MarkItDown is a Python tool that converts various file formats into Markdown and integrates with LLM applications via an MCP server for enhanced text analysis and document processing.
Awesome MCP › Other MCP Servers
Unity MCP is a plugin and server designed to bridge Large Language Models (LLMs) with the Unity Editor, enabling AI-driven interaction and automation within Unity through the Model Context Protocol (MCP). This project allows LLMs to understand and utilize Unity's tools and interfaces as a user would, facilitating advanced workflows, rapid prototyping, and AI integration in game development and other Unity projects. Unity MCP supports a wide range of AI tools that interact with various Unity components such as GameObjects, Editor states, Prefabs, Assets, Scenes, Materials, Shaders, Scripts, and Components. These tools enable operations like creating, modifying, finding, and deleting objects and components, managing editor states, running tests, and more. The system is extensible, allowing developers to add custom tools directly in their Unity project codebase, which can then be exposed to AI or automation clients. Unity MCP currently works within the Unity Editor and aims to extend its features to player builds in the future. It supports integration with popular LLM clients like Claude and Cursor through an integrated AI Connector window, and also allows custom clients. Installation requires .NET 9.0 and OpenUPM-CLI, with the package added via OpenUPM. The project emphasizes ease of use, with a clear setup process and a user interface for connecting and configuring MCP clients. Unity MCP is actively maintained with support for multiple Unity versions and continuous integration workflows. Overall, Unity MCP is a powerful tool for developers looking to leverage AI capabilities within the Unity environment, enhancing productivity and enabling new possibilities for AI-driven game development and automation.
https://github.com/IvanMurzak/Unity-MCP
MarkItDown is a Python tool that converts various file formats into Markdown and integrates with LLM applications via an MCP server for enhanced text analysis and document processing.
A curated collection of Model Context Protocol (MCP) servers that enable AI models to securely interact with local and remote resources through standardized server implementations.
The Model Context Protocol Servers repository offers reference implementations and third-party integrations that demonstrate how MCP enables Large Language Models to securely access and interact with diverse tools and data sources.
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Headroom is a context compression layer for AI agents, reducing token usage by 60-95% while preserving accuracy, implemented as a library, proxy, and MCP server.
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