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qpd-v-ragdocs

Integrates semantic search and retrieval of documentation using a vector database (Qdrant), enabling efficient access to large document collections.

Score
94.3022 signals
Evidence
136 stars · 60 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 Docs, catalogued on PulseMCP. Integrates semantic search and retrieval of documentation using a vector database (Qdrant), enabling efficient access to large document collections.

When to use it

Integrates semantic search and retrieval of documentation using a vector database (Qdrant), enabling efficient access to large document collections.

Notes

Listed from the PulseMCP registry. The registry does not state a license. Check it before production use.