mcp-qdrant-embedding-search
MCP server that searches documents in Qdrant using embeddings from LMStudio. Takes a text query, converts it to a vector via LMStudio's OpenAI-compatible API, and performs semantic search in Qdrant.
- Score
- Unranked
- Evidence
- No signals yet
- 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.
Alternatives · MCPs
- zilliz-claude-context12,463 stars · 917 forks99.277
- rahilp-second-brain737 stars · 102 forks97.314
- context-portal765 stars · 78 forks97.218
What it is
MCP server that searches documents in Qdrant using embeddings from LMStudio. Takes a text query, converts it to a vector via LMStudio's OpenAI-compatible API, and performs semantic search in Qdrant.
When to use it
MCP server that searches documents in Qdrant using embeddings from LMStudio. Takes a text query, converts it to a vector via LMStudio's OpenAI-compatible API, and performs semantic search in Qdrant.
How to install / invoke
See Glama for the install config.
Notes
Listed from the Glama MCP registry.