DocMCP
Indexes technical documentation on a local vector database and integrates with AI IDEs for semantic search.
About
DocMCP is a system designed to crawl, process, and query documentation, leveraging AI-powered embeddings for enhanced semantic search capabilities. It crawls documentation websites, converts HTML content to clean Markdown, generates vector embeddings using AWS Bedrock, and integrates seamlessly with Cursor IDE through MCP tools. This allows developers to quickly find relevant information within large documentation sets, improving productivity and knowledge discovery.
Key Features
- Provides built-in MCP tools for AI agent integration.
- Converts HTML to clean Markdown with metadata extraction.
- Generates embeddings using AWS Bedrock for semantic searching.
- Automatically crawls documentation sites with customizable depth and rate limiting.
- Tracks and manages document processing jobs with detailed progress reporting.
- 3 GitHub stars
Use Cases
- Indexing documentation for local development environments.
- Providing semantic search capabilities within IDEs like Cursor.
- Building AI agents that can query documentation for information.
Sponsored