Uptodoc MCP Server

Overview

uptodoc is a lightweight MCP (Model Context Protocol) server designed to bridge the gap between IDE‑integrated AI assistants—such as GitHub Copilot, Roocode, Cursor, or Windsurf—and custom documentation sources. By running locally and exposing a simple MCP interface, it lets developers keep their AI tools informed with the most current, project‑specific, or proprietary documentation that would otherwise be inaccessible to generic cloud assistants.

The core problem it solves is the mismatch between an AI assistant’s knowledge base and the actual libraries or frameworks a project uses. Most assistants rely on public APIs or static documentation, which can become stale or fail to reflect internal conventions. With uptodoc, developers point the assistant at a dedicated documentation endpoint (e.g., a GitHub repository or an internal server), and the AI can query that source in real time. This ensures suggestions, code completions, and explanations are grounded in the exact version of a library that the project depends on, reducing errors and improving developer confidence.

Key features are intentionally simple yet powerful. The server runs via a standard Node.js environment, automatically launched by the IDE when configured in the MCP settings. It exposes a single environment variable that can be set to any HTTPS location hosting markdown or structured docs. The MCP client (the IDE’s AI assistant) can then invoke a directive in prompts, triggering the server to fetch and return relevant snippets. Because it operates over stdio, integration requires no network configuration beyond the endpoint URL, keeping the setup lightweight and secure.

Typical use cases include:

• Project‑specific documentation – A team maintains an internal guide for a proprietary API; the assistant can pull that guide on demand.
• Version‑specific queries – When a project upgrades to a newer library version, the assistant instantly reflects the updated API surface.
• Custom knowledge bases – Organizations can host domain‑specific best practices or coding standards, allowing AI assistants to surface that knowledge without exposing it publicly.

In practice, a developer simply adds the uptodoc server configuration to their IDE settings, starts the MCP server, and then uses the phrase in their chat or code completion prompts. The assistant transparently retrieves the requested documentation and incorporates it into its responses, delivering context‑aware help that feels native to the project environment. This tight integration enhances productivity and reduces friction when working with complex or evolving codebases.