关于
This powerful system facilitates efficient document retrieval by leveraging vector search. It intelligently ingests and chunks markdown documents, preserving their hierarchical structure, then generates high-quality contextual embeddings using Voyage AI's API. These documents and their corresponding embeddings are stored in MongoDB with parent-child relationships, enabling advanced semantic search. The tool offers a FastMCP server, allowing seamless integration with MCP clients for comprehensive document search capabilities, and supports flexible configuration of vector dimensions and chunking strategies.
主要功能
- Ingests and chunks markdown documents with hierarchical headers
- Generates embeddings using Voyage AI's contextual embeddings API
- Stores documents and embeddings in MongoDB with parent-child relationships
- 1 GitHub stars
- Supports configurable vector dimensions and chunking strategies
- Provides a FastMCP server for semantic document search
使用案例
- Performing semantic document search for information retrieval
- Integrating vector search capabilities into MCP clients like Claude Desktop
- Building knowledge bases for AI applications requiring contextual document access
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