"k6" matching MCP servers:

将 pgvector 知识库检索能力封装为标准 MCP 服务器，支持 Tools、Resources 和 Prompts，使 Claude Desktop 等客户端可通过自然语言查询知识库。

A local-first knowledge base for LLM coding agents that indexes repository documentation, concept ontology, and build targets into Qdrant and exposes retrieval as MCP tools (search, get, list sources, reindex).

A local-first knowledge base server that enables AI clients to store, retrieve, and manage documents using semantic search. Provides privacy-focused, offline-capable memory for AI assistants with tools for ingesting, querying, updating, and deleting knowledge.

Enables searching and retrieving Claude Code conversation history via hybrid semantic and keyword search, allowing the agent to access its own past interactions.

HTTP MCP gateway for a learning corpus that enables remote agents to perform semantic search, graph queries, and routing via Pinecone and Neo4j without direct database credentials.

An MCP server aimed to be portable, local, easy and convenient to support semantic/graph based retrieval of txtai "all in one" embeddings database. Any txtai embeddings db in tar.gz form can be loaded

Enables a support bot to answer FAQ questions from a local vector store, with admin tools to add, list, and delete knowledge entries while enforcing read-only versus admin bearer-token permissions.

Standalone MCP server exposing agentic-RAG tools (hybrid search, article retrieval, category listing) over a pgvector-backed knowledge base with bearer-token auth, designed for deployment on Render.

Enables AI tools to search and manage a private local knowledge base via MCP or HTTP, using local Chinese semantic retrieval without sending data externally.

Enables storing and searching personal notes, documents, and snippets using semantic search and RAG capabilities across Claude Desktop, VS Code, and Open WebUI.

HTTP MCP gateway for a learning corpus with Pinecone, Neo4j, and agentic router, enabling remote agents to query via tools like route_query, query_namespace, graph_query, etc.

Read-only MCP server with hybrid search combining dense semantic and sparse keyword retrieval via Qdrant, enabling document querying and fetching for ChatGPT Deep Research.