Rust Docs
Provides accurate Rust code suggestions for AI assistants by fetching current crate documentation and using LLMs to provide context.
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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.
Características Principales
- 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
Casos de Uso
- 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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