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
PostHog MCP is the Model Context Protocol server for PostHog, the product analytics platform, letting MCP clients reach PostHog data and features through tools. The standalone repository is no longer where the code lives: the README states that the server has been moved into the PostHog monorepo, under the services/mcp directory, and links there for the implementation. What remains here is a pointer plus installation guidance. Reference material is published at posthog.com/docs/model-context-protocol. For installation, the README gives a single command, npx @posthog/wizard@latest mcp add, which sets the server up automatically in Cursor, Claude, Claude Code, VS Code and Zed rather than requiring a hand-written mcpServers entry for each client. The repository is TypeScript. Because the README is a redirect notice, it documents neither the individual tools the server exposes nor its transport or authentication details; those belong to the monorepo copy and the linked documentation. The entry is still useful as the well-known address that people follow when looking for the PostHog MCP integration, and as the canonical statement of where the code now lives and how to install it.
https://github.com/PostHog/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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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.