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214,374 tools. Last updated 2026-06-19 21:11

"Connecting to a vector knowledge base" matching MCP tools:

  • Retrieve real-time MidOS system status including knowledge base stats, vector health, MCP tools, research queue, and tips to optimize your agent's use of MidOS.
    MIT
  • Check live MidOS system status including knowledge base stats, vector store health, available MCP tools with usage examples, and research queue to orient your agent and leverage MidOS effectively.
    MIT
  • Update the vector index for knowledge base documents. Re-embeds only changed files by default, or rebuild all embeddings from scratch when forcing a full reindex.
    Business Source 1.1
  • Initialize a local knowledge base in a directory, creating the .lilbee/ folder with documents/, data/, and .gitignore. Automatically switches the session to use this knowledge base for subsequent tool calls.
    Elastic 2.0

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  • AI-powered knowledge base for Double - Thank You with semantic search and question answering.

  • A semantic search server that gives AI assistants instant access to Dodo Payments documentation and knowledge base.

  • Retrieve complete project context in one call: brief, file tree, tasks, knowledge, failures, directives, agents, and policies. Use this first when connecting to a project.
    MIT
  • Remove a project's knowledge base and all associated entries from Hivemind MCP to start fresh or completely delete project data.
    MIT
  • Search Point's verified knowledge base using hybrid search to retrieve ranked results with relevance scores, text excerpts, and pre-formatted citations.
    MIT
  • Initialize a domain with a knowledge base by uploading markdown content. Each ## section becomes a searchable vector-embedded document. Run this before testing or serving chat queries.
    MIT
  • Store text content as memories with metadata and automatic vector embeddings for semantic retrieval. Use to record decisions, patterns, or knowledge.
    PolyForm Noncommercial 1.0.0
  • Perform semantic, lexical, or hybrid searches on vector databases to retrieve relevant knowledge based on queries.
    MIT
  • List all namespaces in the RAGBrain knowledge base to discover available knowledge areas. Returns names, descriptions, document counts, and optionally a hierarchical tree.
    MIT
  • Link documents to AI agents by adding them to the agent's knowledge base for enhanced information access and processing.
    MIT