"knowledge" matching MCP servers:

A local MCP server that gives LLMs long-term memory by indexing code, infrastructure, logs, and docs into a queryable graph. It enables semantic and structural search, evidence-backed reasoning, and tracked plans that persist across sessions and teams.

Enables LLM agents to maintain structured long-term memory and knowledge using SQLite, with graph storage and relational query tools for persistent context.

A modern community hub with forum and knowledge base. Native MCP built-in, ready for the next era of internet culture.

Enables AI assistants to manage Sable AI voice agents, journeys, knowledge bases, deployments, and analytics through natural language, plus observability via HyperDX.

Your agents, briefed. Not flooded. Self-hosted context compiler: git-backed team knowledge served to coding agents as token-budgeted bundles over MCP.

Coordination for parallel coding agents: TTL file claims stored in the git common dir (visible across all worktrees), enforcement hooks that block colliding edits, agent presence, handoff notes, and a git-committed lessons knowledge base with BM25 search. Single static Go binary — no server, no database.

MCP server that indexes Markdown, Word, HTML, and PDF documents into a SQLite knowledge graph with CJK+Latin full-text search and cross-document reference tracking. Runs drift audits to surface stale policies, conflicting research claims, superseded ADRs, and undocumented code exports.

I gave Claude a mass grave of 200 markdown files and now it remembers my entire project between sessions. No cloud, no API keys, one 10mb Go binary, and private. Stateless Agent Memory Engine is your synapse to the CLI.

Persistent memory for AI agents as a single Go binary: hybrid recall, self-building knowledge graph, and a live TUI dashboard. Zero infra, offline-first — works with Claude Code, Cursor, Codex, OpenCode, and any MCP client.

Content-addressed code graph that produces ranked context for AI agents in one call. 22 MCP tools across indexing, blast radius, test scope, semantic diff, runtime traffic, and feedback-aware context packing. Incremental updates via Merkle DAG (no re-indexing). GCF wire format saves 84% tokens vs JSON

Enables AI coding assistants to search and retrieve information from a locally ingested knowledge base using hybrid search, grounded in user-curated documentation.

Connect to your TTRPG campaign's repository and database. Instead of retrieving prose, its 48 tools (20 read, 28 write) return typed state: 14 entity schemas (NPCs, factions, locations, sessions, lore), relationship and knowledge-graph queries, wiki blocks, and a narrative-state bundle of open threads and canon facts.

Serves a folder as an MCP knowledge server: it indexes text, code, PDFs, office documents and audio or video, then answers search and ask calls with citations that name the file, the line range, the page or the time range. Runs fully local with Ollama by default; Mistral, OpenAI, Gemini and Anthropic are optional providers.

A frontier knowledge base that’s minimal extensible and agent-native. Built to keep your team’s shared context current and inspectable.

Enables AI agents to orchestrate 100+ security tools over MCP for authorized penetration testing, including recon, scanning, exploitation, attack-chain planning, and knowledge-base retrieval.

Self-hosted knowledge mesh with built-in MCP server enabling AI agents to search and retrieve notes across federated hubs.

A self-hosted personal context server that unifies knowledge base, retrieval, credential management, and agent memory via MCP, with a built-in notes app for human oversight.

🧠 High-performance persistent memory system for Model Context Protocol (MCP) powered by libSQL. Features vector search, semantic knowledge storage, and efficient relationship management - perfect for AI agents and knowledge graph applications.

A memory, docs, and repo context layer for engineering agents, providing typed persistent memory, RAG document retrieval, and repository-aware tools to recall decisions, runbooks, and operational knowledge across sessions.

An MCP server that lets AI agents read and write a self-hosted TriliumNext knowledge base over its ETAPI, enabling note capture, structured table maintenance, and search.