Rust Docs
Provides accurate Rust code suggestions for AI assistants by fetching current crate documentation and using LLMs to provide context.
About
Rust Docs leverages the Model Context Protocol (MCP) to enhance AI coding assistants with up-to-date information about Rust crates. By running an instance for a specific crate, the server provides a tool that LLMs can use to query the latest documentation before generating code. This significantly improves the accuracy and relevance of AI-generated Rust code, reducing manual corrections and accelerating the development process. It supports semantic search using OpenAI embeddings, LLM summarization, and caching for efficient operation.
Key Features
- Fetches and caches documentation for specific Rust crates.
- Uses OpenAI embeddings for semantic search over documentation.
- Leverages LLMs to provide concise answers based on documentation context.
- Integrates with MCP clients via stdio.
- Supports specifying crate features for documentation generation.
- 0 GitHub stars
Use Cases
- Improving the accuracy of Rust code suggestions in AI coding assistants.
- Providing LLMs with up-to-date context for Rust crate APIs.
- Enabling AI assistants to answer specific questions about Rust crate usage.
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