"knowledge" matching MCP servers:

Enables grounded, dated research from a curated AI-knowledge repository, offering free BM25 retrieval and a research loop that combines the knowledge base, curated sources, and the open web with tiered citations.

Local knowledge engine for codebases with hybrid search, knowledge graph, and interaction tracking, enabling Claude Code to search and interact with project knowledge locally.

Long-term memory for AI agents. Compiles conversations into a structured knowledge base with Claim/Evidence model, source provenance, append-only timeline, and contradiction detection. Multi-path retrieval (Exact + BM25 + Graph + weighted RRF + reranker) — 96.6% R@5 on LongMemEval-S, zero vector dependencies.

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.

An MCP server that acts as a knowledge engine for software projects, delivering relevant context at the start of a task and accumulating knowledge at its end through tools like start_task, context, finish_task, remember, and search, with a file-based source of truth and optional semantic retrieval via Graphiti/Neo4j.

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.

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.

Automatically organizes and merges learned CS knowledge into a graph structure using Claude for entity/relation extraction and SQLite for storage, with tools for ingestion, querying, merging, and managing nodes and edges.

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.

An MCP-native evidence retrieval platform that ingests source material, builds lexical and vector indexes, performs hybrid retrieval, and returns structured evidence packages for AI assistants.

Enables searching and reading AWS knowledge from sources the official AWS Knowledge MCP Server does not index, including re:Post community Q&A, kiro.dev documentation, and AWS Builder Center posts.

A personal knowledge base MCP server that allows AI assistants to manage notes, tasks, and ideas through tools, resources, and prompts.

Enables coding agents to query a team knowledge base via MCP, performing semantic search and asking questions that return grounded, citation-backed answers from ingested documents.

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 evidence-based retrieval across official BMC Helix product documentation and isolated private project knowledge, with product, version, project, source, and section provenance. Supports version-aware multi-product indexing, hybrid lexical and optional semantic search, and read-only access to local evidence without touching live Helix systems.

Dense Knowledge is a small local server for Model Module Protocol (MMP) files. It gives language models a persistent research memory without requiring a database, embeddings, or a hosted service.

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.