Docs‑to‑MCP Server

The docs‑to‑mcp‑cli server transforms a collection of Markdown files into a fully‑functional Model Context Protocol (MCP) service. By exposing documentation as an MCP endpoint, developers can let AI assistants query and browse their technical docs without writing custom integrations. The server is self‑contained: a single CLI command bundles the entire documentation set, generates the necessary MCP tooling, and produces an executable package that can be launched with . This eliminates the need for separate web servers or database layers, making it ideal for quick prototypes and lightweight production deployments.

At its core, the server offers three intuitive tools: , , and . returns a catalog of all documents along with a short preview, allowing the AI to present users with relevant titles. fetches the full content of a requested file, enabling deep dives into specific sections. performs fuzzy matching across the entire corpus, which is particularly useful when a user remembers only part of a topic. These tools are designed to mirror common human interactions with documentation—browse, read, and search—while fitting neatly into the MCP command‑response paradigm.

The value for developers lies in the seamless integration with AI workflows. Once deployed, any MCP‑compatible assistant can connect to the server and treat the documentation as a first‑class data source. For example, a chatbot can answer “How do I configure the API client?” by querying for relevant snippets and then presenting a concise, context‑rich response. In larger teams, the server can be updated automatically from a documentation repository, ensuring that assistants always reference the latest information. Because the output is a self‑contained Node.js package, it can be versioned and distributed just like any other library.

Real‑world scenarios include internal knowledge bases, API reference guides, and onboarding documentation. In a software company, the server can power an AI pair programmer that pulls examples directly from the repo. In open‑source projects, maintainers can expose their README and wiki files to community bots that answer questions without leaving the chat platform. The CLI’s flexibility—glob patterns, custom tool names, and output directories—lets teams tailor the server to fit existing folder structures or naming conventions.

What sets this MCP server apart is its zero‑dependency footprint and the fact that it turns static Markdown into a live, queryable API with no database or search engine setup. Developers can focus on writing documentation; the tool handles packaging, indexing, and exposing it through MCP. The result is a lightweight, maintainable bridge between human‑readable docs and AI assistants that can reason over them in real time.