Qdrant MCP Server

Example Use Cases

• 1

  Semantic search over codebases and git history with local-first privacy.

• 2

  Perform hybrid search combining semantic and keyword queries across multiple repositories.

• 3

  Configurable prompts and incremental indexing for efficient and customizable workflows.

Description

Qdrant MCP Server provides semantic search capabilities by integrating Qdrant vector database with various embedding providers like Ollama, OpenAI, Cohere, and Voyage AI. It supports advanced features such as code vectorization with AST-aware chunking, git history semantic search, hybrid search combining semantic and keyword methods, and incremental indexing for efficient updates. The server prioritizes privacy by enabling local embeddings and vector storage, and offers flexible deployment options including local stdio and remote HTTP transport with API key authentication.