"An overview of knowledge graphs and their applications" matching MCP servers:

A self-hosted, MIT-licensed MCP server that securely connects private documents and markdown files to LLMs. It provides a lightweight, local-first RAG infrastructure compatible with any MCP-enabled AI client or framework.

Vendor-neutral MCP server for knowledge retrieval across repositories, offering stable tools for searching, getting, and listing documents with hybrid lexical and optional semantic search.

A knowledge base MCP server that aggregates team knowledge from multiple sources into Postgres. It provides hybrid search (full-text + vector + RRF) via MCP tools, and enables direct recording of decisions, learnings, and pitfalls.

Enables AI agents and MCP clients to search, retrieve, and read documents across unified knowledge sources including ShowDoc, GitHub, Gitee, ZenTao, Evernote, and Tencent Docs. It also supports connecting external MCP servers as additional knowledge sources.

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.

Search 47,000+ marketing agencies and get AI-matched with fitted agencies, from Pick an Agency.

An improved implementation of persistent memory using a local knowledge graph with a customizable --memory-path. This lets Claude remember information about the user across chats.

Records a sale of a vehicle, equipment or stock and produces a printable bill of sale with signature lines. Drafts can be edited and finalized into a frozen signing copy rendered as Markdown or self-contained HTML for print-to-PDF.

Provides a read-only MCP interface to the Santismm Knowledge Platform, offering tools to retrieve curated content on engineering, AI patterns, architectures, governance, and agent taxonomy with structured output in English, Spanish, and Portuguese.

A Model Context Protocol (MCP) server that gives AI assistants the ability to search, analyze, and extract knowledge from YouTube videos.

Enables building client statements of account from existing invoices, credit notes, and deposits, with aged outstanding balances, PDF/plain-text output, and drafted payment chasers at friendly, firm, or final levels.

MCP server with 12 tools for design, UX, conversion, and product knowledge from Frontend Masters courses by Paul Boag and Sarah Drasner, enabling audits, accessibility checks, layout recommendations, and more.

Enables Claude clients to access notes, guidance, projects, and search from a knowledge library, with explicit-save write tools for creating, updating, and appending content only when the user approves.

Enables checking project files like Dockerfile, .nvmrc, and CI workflows to determine whether pinned runtime, database, and OS versions are still supported, providing end-of-life dates, latest patches, and upgrade targets for 470+ products.

Enables Claude to save, retrieve, update, search, and organize personal ideas and reusable analytical frameworks in a private SQLite-backed knowledge base. Supports local desktop use or always-on access across a user's own devices over a private network.

A production-grade RAG server with a centralized knowledge base, offering both MCP and REST APIs for semantic search, document ingestion, and RAG-based answers.

Exposes a knowledge base to LLM clients through tools, resources, and prompts.

A read-only MCP server that enables AI clients to search a knowledge base and retrieve complete source documents via narrow search and fetch tools.

This MCP server provides persistent memory integration for chat applications by utilizing a local knowledge graph to remember user information across interactions.

Transforms YouTube into a queryable knowledge source with search, video details, transcript analysis, and AI-powered tools for summaries, learning paths, and knowledge graphs. Features quota-aware API access with caching and optional OpenAI/Anthropic integration for advanced content analysis.