Documentation MCP Server

The Documentation MCP Server is a purpose‑built bridge that lets Claude and other LLM assistants fetch, parse, and return precise excerpts from the official documentation of leading AI libraries—LangChain, LlamaIndex, and OpenAI. In practice it solves the friction of “I need a quick reference” by turning a natural language query into a focused web search, HTML extraction, and concise answer that can be injected directly into the conversation. This eliminates the need for developers to leave their IDE or chat window, copy‑paste snippets, and manually sift through docs.

At its core the server exposes a single tool, , which accepts three parameters: a search query, the target library, and an optional character limit. Under the hood it queries Google via the Serper API with a site‑specific filter, retrieves the resulting page, and uses BeautifulSoup to pull out only the main content blocks. The extracted text is then trimmed to the requested length and returned as a JSON payload that Claude can present in‑line. This flow keeps the assistant’s context small, respects token limits, and guarantees that the information is sourced from the official documentation rather than unverified web content.

Key capabilities include:

• Library‑specific searches that restrict results to a single documentation domain, ensuring relevance.
• Smart extraction that discards navigation and ads, focusing on the core content of a page.
• Configurable response size so developers can request just enough detail for their use case, from a single sentence to a paragraph.

Real‑world scenarios abound: a data scientist asking Claude for the exact signature of LangChain’s interface, a backend engineer needing to verify LlamaIndex’s initialization parameters, or an AI product manager querying OpenAI’s API limits—all without leaving the chat. By integrating with Claude Desktop, the server becomes a first‑class tool in any AI‑augmented workflow, enabling rapid prototyping, documentation‑driven development, and on‑the‑fly learning.

What sets this MCP server apart is its lightweight, plug‑and‑play nature. It requires only a Serper API key and Python 3.11+, no heavy infrastructure or custom indexing pipelines. Developers can drop it into their existing MCP ecosystem, expose the tool, and immediately gain a reliable source of up‑to‑date documentation that keeps pace with library releases. This turnkey solution empowers teams to embed authoritative knowledge directly into conversational AI, streamlining debugging, onboarding, and continuous learning.