Search for memories by content in a Qdrant collection to retrieve personal information for analysis.
Apache 2.0
525,518 tools. Updated 2026-09-06 21:34
"Qdrant MCP Server" matching MCP tools:
- Confirm the Nordic MCP server process is responding. Use at the start of a session to verify server reachability before other calls.MIT
- Check Qdrant connectivity, active embedding model, reranker status, and server version to confirm correct RAG configuration. Start here when the pipeline seems broken or unreachable.Apache 2.0
- Retrieve all distinct entities (users, agents, runs) that currently hold memories. Uses server-side aggregation via Qdrant Facet API with scroll+dedupe fallback for compatibility.MIT
- Retrieve a list of all collections in your Qdrant server to view and manage available vector spaces.Apache 2.0
- Retrieves metadata for all Qdrant collections, including point counts and vector dimensions, in markdown or JSON format.MIT
Matching MCP Servers
- AlicenseAqualityCmaintenancePython MCP server for vector search using Qdrant vector database and Ollama embeddings, with advanced query techniques like query expansion, HyDE, and reranking.22MIT
mcp-server-qdrantofficial
AlicenseBqualityCmaintenanceThis repository is an example of how to create a MCP server for Qdrant, a vector search engine.21,516Apache 2.0
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- Check the status of Docker daemon, Qdrant, and MCP server to verify they are running properly.MIT
- Search for memories in Qdrant by content. Retrieve stored memories for analysis or personal information.Apache 2.0
- Search for memories by content in a specified Qdrant collection to retrieve user information or enable further analysis.Apache 2.0
- Retrieve recent logs from a Hephaestus service (qdrant, server, or monitor) with configurable line count.MIT
- Search for semantically similar documents stored by LlamaIndex in Qdrant to retrieve relevant context and knowledge base content.Apache 2.0
- Retrieve a specific point from a Qdrant collection by its ID. Provide the point ID and collection name to fetch the exact stored data.Apache 2.0
- Save new documents or text chunks to a Qdrant vector database for later retrieval, adding information to a knowledge base with metadata support.Apache 2.0
- Delete a specific point in a Qdrant collection by providing its unique ID and the collection name.Apache 2.0
- Retrieve all available Qdrant collections for managing and organizing vector database content in the Better Qdrant MCP Server.MIT
- Upload and process documents into a Qdrant collection using specified embedding services like OpenAI or Ollama. Define text chunk size and overlap for efficient semantic search integration.MIT
- Remove a specific collection from the Qdrant vector database to manage storage and optimize semantic search operations effectively.MIT
- Submit an MCP server URL to the MCP Servers Directory for inclusion in the public registry, enabling discovery and integration.-
- Clear cached OAuth credentials to force re-authentication for Chrome Enterprise Premium MCP server calls.Apache 2.0
- Check if the Cakemail MCP server is operational. Returns health status, server version, and endpoint count.MIT
- Get MCP server environment details: version info for server, FastMCP, MCP protocol, and Python runtime. Use for debugging and compatibility checks.Apache 2.0