"Qdrant MCP Server" matching MCP servers:

Provides semantic search capabilities using Qdrant vector database with multiple embedding providers, including hybrid search, code indexing, and git history search. Adds optional time-based recency scoring to search results.

Enables storing, semantically searching, listing, and deleting text records in any Qdrant collection using plain vectors compatible with default LangChain and n8n setups.

Enables AI assistants to interact with a Qdrant vector database, including embedding generation and vector search operations.

Enables reading news numerologically by extracting numbers, computing gematria, finding resonance patterns via hybrid search in Qdrant, and generating daily numerology forecasts.

Gives AI agents a persistent vector memory by embedding text with Ollama and storing it in Qdrant, so they can save, batch-save, semantically search with payload filters, and delete memories across collections.

Q-learning memory for Claude Code. Persistent memory that learns which context helps you get work done. Memories that lead to productive sessions (commits, PRs, tests) earn higher retrieval rank automatically. 16 MCP tools, hybrid BM25 + vector + Q-value scoring, local-first with Qdrant + FastEmbed.

Self-hosted AI workspace exposing semantic document search (RAG via Qdrant and Apache Tika), long-term user memories, and multi-provider AI chat as MCP tools and resources.

Enables indexing a folder of documents or uploaded files into a Qdrant vector store and retrieving relevant chunks with cosine similarity, metadata filters, and heuristic reranking. Exposes rag_stats, rag_search, and rag_index tools over HTTP and Streamable HTTP MCP so clients can fetch ready-to-use context blocks without any built-in chat model.

Gives Claude Code persistent cross-session memory backed by self-hosted Qdrant vector storage, optional Neo4j knowledge graphs, and Ollama embeddings, using either an Anthropic subscription token or a fully local LLM for fact extraction. Exposes 11 tools for adding, searching, updating, and deleting memories plus graph entity exploration, along with session hooks that inject context on startup and save summaries on exit.

Enables Claude Code to use a self-hosted persistent memory layer backed by Qdrant, Neo4j, and Ollama, with Anthropic or Ollama as the main LLM. It provides MCP tools to add, search, update, delete, and graph memories across sessions.

Enables Claude Code to persist, search, update, delete, and graph-link memories across sessions using self-hosted Qdrant, Neo4j, and Ollama, with Claude or Ollama as the main LLM.

Enables Claude Code to store, search, update, and delete persistent memories and knowledge-graph entities across sessions, backed by self-hosted Qdrant, Neo4j, and Ollama with optional Anthropic or fully local LLM inference. It also provides session hooks and a prompt that automatically inject relevant context at startup and save conversation summaries at exit.