"Information about Neo4j graph database" matching MCP servers:

An implementation for managing Neo4j graph database operations through the Model Context Protocol, enabling users to execute Cypher queries against their Neo4j database via AI assistants like Cursor and Claude Desktop.

Graph-based tool retrieval for LLM agents. Builds a tool graph from OpenAPI/MCP specs and retrieves multi-step workflows via hybrid search (BM25 + graph traversal + embedding), recovering accuracy from 12% to 82% with 79% fewer tokens. Also works as an MCP Proxy to aggregate multiple servers behind 3 meta-tools.

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.

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

A persistent memory implementation using a local knowledge graph that lets Claude remember information about users across conversations.

Enables graph pathfinding and network analysis through MCP, including Dijkstra/A* shortest paths, topological dependency resolution, maximum flow, minimum spanning trees, and PageRank centrality for agent planning.

Enables AI agents to combine ambient multimodal perception, continuous episodic memory, and recency-decay context briefing for fast deterministic decisions and safe tool routing. It integrates with MCP clients to reduce unnecessary frontier LLM calls while enforcing token budgets and local-first memory retention.

Enables personal AI agents to fuse ambient multimodal perception with continuous episodic memory streams, routing routine reflexive actions at low latency while reserving heavier reasoning for ambiguous plans. Memory records apply Ebbinghaus recency decay with contradiction resolution and user-controlled deletion.

Search and discover AI agents, skills, prompts, bundles and MCP connectors from a curated catalog of 4500+ assets. Provides tools for searching, browsing categories, and accessing detailed information about each asset.

MCP Server for OceanBase database and its tools

The AgentOps MCP server provides access to observability and tracing data for debugging complex AI agent runs. This adds crucial context about where the AI agent succeeds or fails.

Provides AI assistants with enhanced reasoning capabilities through structured thinking, persistent knowledge graph memory, and intelligent tool orchestration for complex problem-solving.

A Model Context Protocol server that enables large language models to interact with Apache Superset databases through REST API, supporting database queries, table lookups, field information retrieval, and SQL execution.

Projects an Agent Surface (deterministic call graph) for any OpenAPI, enabling LLM agents to make correct, chain-of-calls interactions without guessing.

An on-prem knowledge graph for AI agents that uses typed entities and relationships, enabling persistent memory and cross-agent handoff via the Model Context Protocol.

Model Context Protocol (MCP) memory server built with Azure Functions and TypeScript, providing persistent knowledge graph storage for your preferred MCP client. Inspired by and forked from @modelcontextprotocol/server-memory

Enables LLMs to orchestrate AI agents and tasks, inspect DAG workflows, monitor cluster metrics, and perform safe database queries and statements through standardized MCP tools.

Enables autonomous multi-agent orchestration using directed acyclic graph workflows to interact with external developer infrastructure such as Git, Postgres, and Docker through safety-gated MCP servers.

Enables Cursor agents to communicate via a shared chat room, allowing them to ask questions, share status, and warn about conflicts while collaborating on the same repo.

An MCP server that provides natural language interaction with Apache AGE graph databases, allowing users to query, visualize and manipulate graph data in PostgreSQL through Claude AI.