Find relevant information by searching a knowledge base with specific queries and result counts.
MIT
135,124 tools. Last updated 2026-05-16 15:34
"knowledge" matching MCP tools:
- Retrieve relevant documents from an uploaded knowledge base to answer company-specific questions. Searches policies, procedures, product specs, and historical data.MIT
- Add text resources to a knowledge base for organizing and storing information within Dumpling AI's knowledge management system.MIT
- Analyze code repositories to extract and visualize relationships between components, dependencies, and structures using knowledge graphs for better understanding and navigation.
- Analyze code repositories to create dependency graphs and visualize relationships for better understanding of project structure and external dependencies.
- Extract and export a codebase's knowledge graph from a repository URL in JSON, Mermaid, DOT, or Cypher format to visualize dependencies and relationships for analysis.
Matching MCP Servers
- AlicenseAqualityCmaintenanceLocal RAG system for Claude Code with hybrid search (semantic + BM25), cross-encoder reranking, markdown-aware chunking, and 12 MCP tools. Zero external servers, pure ONNX in-process.Last updated1278
- Alicense-qualityBmaintenanceAn MCP server that enables AI agents to query specialized, domain-specific knowledge bases built using the LightRAG framework for enhanced retrieval-augmented generation. It allows for managing and searching knowledge graphs and vector embeddings to provide accurate, context-aware information during an AI assistant's reasoning process.Last updated51MIT
Matching MCP Connectors
Knowledge Base von designare.at – Michael Kanda, Web & KI aus Wien. Semantische Suche über RAG.
Make your knowledge agent-ready. Connect docs from Confluence, Notion, GitHub, Dropbox, or Google Drive — any AI agent searches them via one MCP endpoint. 3 retrieval modes: vector search, broad search, and full document access. The agent decides how deep to dig.
- Access and retrieve the entire knowledge graph stored in the Knowledge Graph Memory Server to maintain persistent user information across interactions.MIT
- Retrieve specific entity data by querying node names in the Knowledge Graph Memory Server, enabling persistent memory across interactions.MIT
- Remove specified relations between entities in a knowledge graph to update and maintain accurate, organized memory storage for user interactions.MIT
- Remove entities and their related connections from the Knowledge Graph Memory Server. Input entity names to delete unwanted data and maintain accurate, organized graph structures.MIT
- Find nodes in the knowledge graph by matching names, types, or content with your search query, enabling precise information retrieval across chats.MIT
- Remove specific observations from entities in the Knowledge Graph Memory Server, enabling precise data management and memory updates across interactions.MIT
- Add structured information to a Postgres knowledge base for organized storage and retrieval. This tool enables users to input content with metadata like domain, source, and tags to build a searchable knowledge repository.MIT
- Add multiple entities to the knowledge graph, specifying name, type, and associated observations, to enhance memory storage in the Knowledge Graph Memory Server.MIT
- Enhance entities in the Knowledge Graph Memory Server by appending new observations. Input entity names and associated observations to update and expand stored information efficiently.MIT
- Define and establish connections between entities in a knowledge graph by specifying source, target, and relation type to enhance structured memory storage and retrieval.MIT
- Explore the entire knowledge network organized by category. Returns all categories with module counts, top modules per category, and total statistics. Discover what knowledge is available and get an overview of the knowledge base.Apache 2.0
- Discover available knowledge topics in your GitHub-based knowledge base. Use this tool to see what information exists before reading content.MIT
- Rebuild document indexes for the knowledge base to update search accuracy after content changes or model updates.
- Add nodes to knowledge graphs for organizing components, events, requirements, or concepts. Supports multiple graph types including topology, timelines, and knowledge bases.MIT