Librarian MCP Server

Librarian MCP Server is a read‑only knowledge base designed to give Large Language Models instant, on‑demand access to structured markdown content. By exposing a lightweight Model Context Protocol (MCP) interface, it lets AI assistants query documentation repositories without the need for custom integrations or costly index‑building pipelines. This solves a common pain point for developers: keeping an LLM up‑to‑date with evolving internal documentation while preserving the original file hierarchy and metadata.

At its core, Librarian loads a directory of markdown files, interprets YAML frontmatter for tags, and builds an in‑memory index that supports three key operations: listing, searching, and retrieval. The server never writes back to the file system; it simply serves content. This read‑only nature guarantees that your source documents remain untouched, while the LLM can pull precise snippets or entire sections as context. The API also supports hierarchical tag inheritance, meaning a file automatically gains the tags of every ancestor , enabling powerful category‑based filtering without duplicate annotations.

Developers benefit from Librarian’s flexible search primitives. A simple, case‑insensitive string query can quickly surface relevant documents, while regular expression searches allow for fine‑grained pattern matching across titles or content. The tag discovery endpoint lists all available tags along with usage counts, giving insight into the breadth of your knowledge base. Because every operation is exposed through MCP, any AI assistant that understands the protocol can plug in without modification—whether you’re using Claude, GPT‑4, or a custom model.

Real‑world scenarios abound: an engineering team can expose internal design docs to an AI teammate, a support bot can fetch the latest troubleshooting guides on demand, or a product manager can query feature specifications during brainstorming sessions. Librarian’s modular architecture—separate modules for configuration, loading, and server logic—makes it straightforward to extend or replace components, such as adding a caching layer or supporting additional metadata formats.

In short, Librarian MCP Server turns any markdown folder into a searchable, tag‑aware knowledge source that AI assistants can consume in real time. Its simplicity, strict read‑only guarantees, and native MCP compatibility give developers a reliable bridge between static documentation and dynamic conversational AI.