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
This project features an open-source Model Context Protocol (MCP) server designed to facilitate the discovery and utilization of Claude Agent Skills across various AI models, including those beyond Anthropic's ecosystem. It implements semantic search capabilities using vector embeddings to identify relevant skills based on task descriptions, adhering to Anthropic's progressive disclosure architecture for efficient skill loading. The server employs a two-package architecture, consisting of a lightweight frontend for instant startup and a more substantial backend that handles vector search, RAG dependencies, and skill processing. This design effectively resolves common timeout issues in environments like Cursor by allowing the frontend to respond quickly while the backend loads in the background. Key features include zero-configuration setup with curated skills from official Anthropic and K-Dense AI repositories, multi-source skill loading from GitHub or local directories, and smart caching for fast, local operation without external API keys. It offers three MCP tools: `find_helpful_skills` for semantic search, `read_skill_document` for retrieving specific skill files, and `list_skills` for inventorying loaded skills. The project aims to democratize access to Claude's powerful Agent Skills system, making specialized functionalities available to a broader range of AI applications and enhancing the utility of MCP-compatible assistants.
https://github.com/K-Dense-AI/claude-skills-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.
World Monitor is an AI-powered, real-time global intelligence dashboard aggregating news and monitoring geopolitical and infrastructure data for unified situational awareness.
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.
OmniRoute is a free AI gateway that connects various AI tools and models from over 230 providers through a single endpoint, featuring token compression, smart auto-fallback, and support for Model C...
This comprehensive curriculum teaches AI engineering from scratch, focusing on building AI algorithms, agents, and MCP servers hands-on, covering everything from mathematical foundations to autonom...
Open source, self-hostable SEO platform that exposes its keyword, rank, backlink and site-audit data to AI agents through an MCP server and a set of companion agent skills.