{"type":"mcp_server","name":"mcp-server-qdrant","description":"This repository provides an example of a Model Context Protocol (MCP) server for Qdrant, a vector search engine, enabling seamless integration between LLM applications and the Qdrant database as a","category":"AI","language":"Python","stars":1479,"forks":42,"owner":"qdrant","github_url":"https://github.com/qdrant/mcp-server-qdrant","homepage":null,"setup":"## Setup\n\n**Using uvx:**\n\n1.  Run the server directly using `uvx` with environment variables for configuration.\n2.  Specify the transport protocol using the `--transport` flag (options: `stdio`, `sse`).\n\n```shell\nQDRANT_URL=\"http://localhost:6333\" \\\nCOLLECTION_NAME=\"my-collection\" \\\nEMBEDDING_MODEL=\"sentence-transformers/all-MiniLM-L6-v2\" \\\nuvx mcp-server-qdrant\n```\n\n**Using Docker:**\n\n1.  Build the Docker container: `docker build -t mcp-server-qdrant .`\n2.  Run the container, mapping port 8000 and setting environment variables.\n\n```bash\ndocker run -p 8000:8000 \\\n  -e QDRANT_URL=\"http://your-qdrant-server:6333\" \\\n  -e QDRANT_API_KEY=\"your-api-key\" \\\n  -e COLLECTION_NAME=\"your-collection\" \\\n  mcp-server-qdrant\n```\n\n**Installing via Smithery:**\n\n1.  Install using the Smithery CLI: `npx @smithery/cli install mcp-server-qdrant --client claude`\n\n**Manual configuration of Claude Desktop:**\n\n1.  Add a configuration block to the `claude_desktop_config.json` file, specifying the command, arguments, and environment variables for either remote or local Qdrant.\n\n**Using with Cursor/Windsurf:**\n\n1. Customize the tool descriptions using environment variables `TOOL_STORE_DESCRIPTION` and `TOOL_FIND_DESCRIPTION`.\n2. Configure the MCP server in Cursor/Windsurf settings, pointing to the running server using the SSE transport protocol (e.g., `http://localhost:8000/sse`).\n3. Consider creating Cursor rules to ensure MCP tools are used when the agent produces new code snippets.","tools":"## Available Tools\n\n1.  `qdrant-store` (Stores information in the Qdrant database with optional metadata.)\n2.  `qdrant-find` (Retrieves relevant information from the Qdrant database based on a query.)","faq":null,"created_at":"2024-12-02T12:07:39+00:00","updated_at":"2025-03-28T13:08:50+00:00","source_url":"https://model-context-protocol.com/servers/qdrant-mcp-server-model-context-protocol","related_articles":[]}