About docs-rs-mcp-server
docs-rs-mcp-server makes Rust documentation from Docs.rs available to MCP-compatible clients. The project is abandoned, though the server remains functional.
Key features
- 01Access to Rust documentation from Docs.rs
Use cases
- 01Consult Rust documentation in an MCP client
- 02Look up Docs.rs references while developing in Rust
MCP support
The MCP server exposes Rust documentation from Docs.rs to compatible clients.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEdocs-rs-mcp-server
MCP Server Implementation for Rust documentation from Docs.rs
Project Status
This project is currently abandoned and not under active development.
However, the server is functional and can be used as-is. Community contributions and forks are welcome, but please be aware that there is no guarantee of future updates or support.
What is this?
This repository provides a Model Context Protocol (MCP) server implementation that exposes Rust documentation from Docs.rs to MCP-compatible clients, such as Claude for Desktop.
How to Use with Claude for Desktop
You can add this server to Claude for Desktop by following the official instructions here:
👉 Model Context Protocol User Quickstart
This guide explains how to configure Claude for Desktop to connect to MCP servers, including how to edit your configuration file and troubleshoot common issues.
Disclaimer
- This project is not affiliated with Docs.rs or Anthropic.
- Use at your own risk. No warranty or support is provided.
For more information about MCP and available servers, visit the Model Context Protocol website.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.