nsantra-rag-document-search
Provides document embedding, semantic search, and citation generation using ChromaDB vector storage with PDF ingestion, configurable chunking, cross-encoder reranking, and automatic source attribution for building knowledge bases and research assistants.
- Score
- 53.9852 signals
- Evidence
- 4 stars · 3 forks
- Last commit
- as last read from GitHub; most reads are from 2 Sep 2026 or later
- Listed
Install
No one-command install. Set it up from its source.
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What it is
MCP server RAG Document Search, catalogued on PulseMCP. Provides document embedding, semantic search, and citation generation using ChromaDB vector storage with PDF ingestion, configurable chunking, cross-encoder reranking, and automatic source attribution for building knowledge bases and research assistants.
When to use it
Provides document embedding, semantic search, and citation generation using ChromaDB vector storage with PDF ingestion, configurable chunking, cross-encoder reranking, and automatic source attribution for building knowledge bases and research assistants.
Notes
Listed from the PulseMCP registry. The registry does not state a license. Check it before production use.