"Understanding Integrated Knowledge Graphs" matching MCP servers:

An 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.

Local 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.

Enables building and querying vector-based knowledge graphs with node and edge management and semantic search.

An MCP server that enables semantic search over a private knowledge base via pgvector, with GitHub OAuth authentication and a RAG pipeline.

A read-only Model Context Protocol server that exposes a semantic knowledge base to AI agents via 27 tools. It enables querying of documents and data integrated from sources like Notion, SharePoint, HubSpot, and Slack.

A personal knowledge MCP server with vector database for the Opencode ecosystem. It enables semantic search, tag organization, and session memory logging, all running locally without external API keys.

Enables querying MaxKB knowledge bases through MCP, supporting vector, hybrid, and full-text retrieval of relevant segments, as well as listing knowledge bases, documents, and workspaces.

Provides LLM clients with a persistent, scalable knowledge graph memory system that supports semantic retrieval, contextual recall, and temporal awareness.

Enables storage and semantic search of facts, and interactive 3D visualization of embeddings via MCP tools.

This server enables AI assistants (CLINE, Cursor, Windsurf, Claude Desktop) to share a common knowledge base through Retrieval Augmented Generation (RAG), providing consistent information access across multiple tools.

Enables semantic search and document management with support for text, PDF, and image uploads using your own Supabase database and OpenAI API keys. Supports multi-tenant deployment on Cloudflare Workers or local hosting.

A memory server for Claude that stores and retrieves knowledge graph data in DuckDB, enhancing performance and query capabilities for conversations with persistent user information.

Enables semantic search across multiple knowledge datasets using FAISS vector embeddings, allowing natural language queries to find relevant documents with fast retrieval.

Enables managing knowledge bases in Open WebUI and retrieving relevant fragments from Qdrant-stored knowledge through an MCP client.

Enables AI assistants to build and query temporally-aware knowledge graphs from conversations and data. Supports adding episodes, searching entities and facts, and maintaining persistent memory across interactions.

Agentic RAG Knowledge Assistant is a secure, tenant-isolated MCP server built with FastAPI, PostgreSQL, and pgvector that enables document ingestion, semantic retrieval, and vector search over PDF, DOCX, and text files through authenticated MCP tools.

A retrieval-only MCP server that searches a vectorized Wangsu Terraform Provider documentation knowledge base and returns relevant snippets with rules to guide the caller's LLM in generating accurate, provider-specific answers. It offloads all inference to the calling client, as it does not invoke any LLM or require API keys on the server side.

Provides read-only, citation-backed semantic search and retrieval-augmented generation over enterprise documents via standardized MCP tools, with local embeddings for privacy.

Enables AI-powered document analysis and querying for project documentation using vector embeddings stored in Redis. Supports document upload, context-aware Q\&A, automatic test case generation, and requirements traceability through OpenAI integration.

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.