Docs MCP Server provides a specialized documentation scraping and retrieval system that enables AI assistants to access library documentation from various sources including GitHub, NPM, PyPI, and web pages. Built with TypeScript, it implements a pipeline architecture that handles document scraping, processing, splitting, and storage with features like semantic markdown splitting, greedy chunk optimization, and version-aware retrieval. The server exposes tools for searching documentation, finding specific versions, listing available libraries, and managing scraping jobs through a well-defined API. Particularly valuable for developers who need AI assistants to reference accurate, up-to-date documentation without leaving their workflow.
Starts a scraping job for documentation from a specified URL and returns a jobId immediately.
Retrieves the current status and progress of a specific job.
Lists recent and ongoing active/completed jobs.
Attempts to stop a running or queued job.
Searches the indexed documentation for a specific library.
Lists all libraries currently indexed in the store.
Checks the index for the best matching version for a library based on a target.
Removes indexed documents for a specific library and version.
Fetches a single URL and returns its content as Markdown.
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