memgraph
High-performance open-source in-memory graph database for GraphRAG, AI memory, agentic AI, and real-time graph analytics. Cypher-compatible, built in C++.
Memgraph is an in-memory graph database built in C++ that offers an MCP server interface for AI agent integration, enabling GraphRAG pipelines, AI memory systems, and agentic workflows. It combines vector similarity search with graph traversals in a single Cypher query, providing sub-millisecond multi-hop graph operations alongside semantic search. The database is fully compatible with Neo4j's Cypher query language and includes 40+ graph algorithms through its MAGE library, making it suitable for real-time AI context retrieval, fraud detection, network analysis, and operational analytics.
Key Features
Use Cases
- 01Building GraphRAG pipelines that combine semantic vector search with structured graph context
- 02Implementing AI memory systems for agentic workflows with persistent graph relationships
- 03Real-time fraud detection using graph pattern matching and community detection algorithms
- 04Network analysis and infrastructure monitoring with sub-millisecond query performance
- 05Text2Cypher AI agent integration using schema introspection for natural language queries
- 06Integrating graph-based context retrieval into LangChain, LlamaIndex, and other agentic frameworks
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memgraph — FAQ
What is the Memgraph MCP server?+
The Memgraph MCP server is an interface that allows AI agents and assistants to interact with Memgraph's in-memory graph database, enabling GraphRAG, AI memory, and real-time graph analytics through Cypher queries. It's part of Memgraph's AI Toolkit and integrates with popular agentic frameworks.
How do I install Memgraph for use with AI agents?+
You can install Memgraph via Docker on Windows, macOS, and Linux, or use native packages for Debian, Ubuntu, CentOS, Fedora, and RedHat. For Kubernetes deployments, official Helm charts are available. Alternatively, try the browser-based Memgraph Playground without any installation.
Which AI clients and frameworks work with Memgraph?+
Memgraph integrates with agentic frameworks mentioned in its AI Toolkit and supports MCP protocol for AI assistants. It provides drivers for Python, C/C++, and WebSocket connections, along with Memgraph Lab for visual query development.
Do I need API keys to use Memgraph?+
No API keys are required to use Memgraph locally or in self-hosted deployments. Memgraph Cloud, the managed service on AWS, requires account creation but offers a fully managed experience across 6 geographic regions.
Is Memgraph free to use?+
Memgraph Community edition is available under the BSL license for free use. Enterprise features including high availability, multi-tenancy, and fine-grained access control require the MEL license.
What are the prerequisites for running Memgraph?+
For Docker installations, you need Docker installed on your system. For native installations, supported Linux distributions (Debian, Ubuntu, CentOS, Fedora, RedHat) or macOS with Lima are required. The database is built in C++ and runs in-memory for optimal performance.
How do I install memgraph?+
Open the source repository on GitHub and follow its README. memgraph is a mcp server — MCP Agents Market links you directly to the official repo.
Is memgraph free?+
memgraph is an open-source project hosted on GitHub. Check the repository for its license and any usage requirements.