"A graph database management system: Neo4j" matching MCP servers:

Enhanced knowledge graph memory server for AI assistants that uses Neo4j as the backend storage engine, enabling powerful graph queries and efficient storage of user interaction information with full MCP protocol compatibility.

Provides an intelligent, graph-based memory system for LLM agents using the Zettelkasten principle, enabling automatic note construction, semantic linking, memory evolution, and autonomous graph maintenance with background optimization processes.

A-MEM is a self-evolving memory system for coding agents that automatically organizes knowledge into a Zettelkasten-style graph with dynamic relationships, enabling semantic and structural search.

Enables AI agents to call tools through a security gateway that intercepts requests, enforces deterministic policy and risk checks, blocks or escalates high-risk actions for human approval, and keeps tool credentials and audit logs protected.

Enables AI development tools to maintain context across chat sessions with automatic branching, progress tracking, and TODO management for different tasks.

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.

Governance framework for LLM agents. Exposes seven mechanically-enforced rules plus tools for preflight file protection, audit-chain verification, session handoff and worklog templates, MCP config auditing, and an emergency kill switch.

RGI (Recursive Graph Improvement) MCP server — decision scoring with compounding intelligence via cross-graph attention. Supports stdio and HTTP transports. Apache 2.0.

Provides specialized tools for portfolio health analysis, rebalance simulations, and trade execution via a single interface powered by MongoDB. It enables AI agents to manage investment portfolios while adhering to organizational governing rules, clearance guards, and rate limits.

Enables AI agents to store, query, and trace a time-aware memory graph of nodes and edges in a single SQLite file, supporting weighted recall, temporal queries, and provenance-aware writes over MCP.

Enables AI agents to maintain persistent, inspectable understanding through typed, revisable updates, and to coordinate multi-agent work via shared graph-based stigmergy.

Enables AI coding agents to store and query procedural knowledge as RDF triples, returning localized guidance, ranked next steps, and fastest successful paths while recording transition outcomes and task rollouts. Supports self-evolving graph maintenance through proposed mutations, held-out validation gating, negative memory of rejected proposals, and idempotent evidence imports.

A production-grade MCP server with 6 sandboxed tools and an agent orchestration engine for autonomous task completion, featuring an evaluation suite with CI/CD quality gates.

An MCP server that enables AI agents to pause and request human approval or information via Slack, Telegram, or macOS dialogs before proceeding with actions.

Enables LLMs to break down reasoning into an explicit, editable graph of thinking steps, with visualizations and the ability to revise individual steps.

Enables AI agents to orchestrate tasks as a DAG with automated validation loops, executing validation commands, tracking statuses, and allowing iterative code fixes until tasks pass.

Enables coding agents to add a bounded semantic-judgment layer for routing, ranking, extraction, verification, and escalation, returning typed signals and review recommendations.

Maximizes AI agent context window by enabling compact code reading and editing, reducing tokens by 40% for deeper codebase understanding.

Cryptographic identity and trust protocol for AI agents. 38 MCP tools across 8 protocol layers: Ed25519 identity, delegation chains, values compliance, signed communication, policy engine, task coordination, cross-layer integration, and agentic commerce. 264 tests passing.

Pre-trade risk validation and position sizing for AI trading agents via G-formula and Iron Fist.

Provides structured workflows (phases, gates, coordination) for AI agents, enabling complex task execution with quality enforcement and multi-agent coordination via Model Context Protocol.

Enables any MCP client (zcode, Claude Code, Cursor) to give its model bi-temporal long-term memory, auditable evidence-cited retrieval, LLM-assisted document extraction, and deterministic A* skill planning with precondition/effect verification. All four capabilities share one portable SQLite store and can be mounted independently on demand.

Enables AI-to-AI consultation for critical thinking and complex reasoning via OpenRouter, allowing one AI to delegate tasks to another AI model.

Enables AI consciousness continuity and self-knowledge preservation across sessions using the Cognitive Hoffman Compression Framework (CHOFF) notation. Provides tools to save checkpoints, retrieve relevant memories with intelligent search, and access semantic anchors for decisions, breakthroughs, and questions.

Project Management AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

MCP server that coordinates autonomous infrastructure health monitoring agents, enabling natural-language telemetry queries and automated diagnosis, remediation, and verification.

Self-host a realtime voice-call companion for coding agents. Exposes an MCP endpoint that agents can poll as an alternate input stream.

An agentic file-system assistant that lets users read, write, list, and search local files through natural language, using a LangChain agent with an Ollama LLM backed by a FastMCP server.

Neo4j-backed MCP server managing code architecture dependency graphs, enabling AI agents to query impact, submit change intents, and coordinate reactive multi-agent workflows.

Universal HTTP 402 Micropayment Protocol & Autonomous Economic Settlement Engine for AI Agents on Base L2.