AI Agent for Neo4j Integration
Seamlessly integrate your Neo4j graph database with Claude Desktop, enabling natural language-driven graph operations. Effortlessly execute Cypher queries, create nodes and relationships, and manage your data with conversational AI. Unlock advanced enterprise graph capabilities and streamline your workflow with secure, scalable, and intuitive database management.
Natural Language Graph Database Operations
Empower your teams to interact with the Neo4j graph database using simple, natural language commands. The integration supports executing Cypher queries, creating nodes, and establishing relationships, all through conversational AI in Claude Desktop. Enhance productivity by eliminating complex query syntax and focusing on business outcomes.
- Conversational AI.
- Interact with your Neo4j database using everyday language, making database management accessible to non-technical users.
- Cypher Query Execution.
- Effortlessly execute all types of Cypher queries—read, create, update, delete—directly through the AI agent.
- Secure Operations.
- Supports parameterized queries to prevent injection attacks and ensures your data is protected during all operations.
- Enterprise Database Support.
- Connect to specific databases in Neo4j Enterprise Edition for granular control and multi-database workflows.
Flexible Node and Relationship Management
Easily create, update, and relate data entities within your Neo4j graph. Specify custom node labels, properties, and relationship types, all using intuitive natural language prompts. The integration ensures seamless data structuring to optimize your graph database for analytics and business intelligence.
- Node Creation.
- Add new nodes with specific labels and properties, supporting all Neo4j data types for maximum flexibility.
- Relationship Management.
- Create and manage complex relationships between nodes, defining types, directions, and custom properties.
- Structured Results.
- Receive query and creation results in a structured format, ready for integration into reports or analytics pipelines.
Enterprise Configuration & Workflow Automation
Customize your Neo4j integration for enterprise environments with robust environment variable support, multi-database targeting, and easy deployment via npx or Smithery. Automate tests and development flows to ensure reliability and scalability for mission-critical applications.
- Enterprise Configuration.
- Set up connections to specific databases, configure authentication, and tailor the environment to your organization's needs.
- Rapid Deployment.
- Deploy instantly using npx or Smithery CLI for effortless onboarding and development.
MCP INTEGRATION
Available Neo4j MCP Integration Tools
The following tools are available as part of the Neo4j MCP integration:
- execute_query
Execute Cypher queries on the Neo4j database, supporting all query types and returning structured results.
- create_node
Create a new node in the graph database with specified labels and properties, returning the created node.
- create_relationship
Create a relationship between two existing nodes with defined type, direction, and properties.
Integrate Neo4j with Claude Desktop Effortlessly
Experience seamless natural language interaction with your Neo4j graph database. Book a personalized demo or start your free trial to unlock advanced graph operations with MCP Neo4j Server.
What is Neo4j MCP Server
Neo4j MCP Server is a set of open-source servers and tools built to integrate the Model Context Protocol (MCP) with Neo4j, the leading graph database. Introduced by Anthropic, the Model Context Protocol (MCP) standardizes interactions between large language models (LLMs) and external services, APIs, and databases—enabling seamless, contextual tool use by AI agents and applications. Neo4j MCP Servers allow LLMs and developer tools to interact directly with Neo4j databases for querying, knowledge graph management, data modeling, and cloud database infrastructure control, all through the MCP standard. These servers include specialized implementations for Cypher query execution, knowledge graph memory, visual data modeling, and Neo4j Aura cloud instance management. Backed by major cloud and AI providers, and supported by frameworks like LangChain, CrewAI, and IDEs such as VS Code, Neo4j MCP Server bridges the gap between advanced AI agents and rich, real-world graph data.
Capabilities
What we can do with Neo4j MCP Server
Neo4j MCP Server enables seamless AI-powered and programmatic interaction with Neo4j databases via the Model Context Protocol. Its suite of servers brings contextual data access, graph modeling, and infrastructure management directly to LLMs, agents, and developer tools.
- Query Graph Data
- Use LLMs or agent frameworks to generate and execute Cypher queries, retrieve subgraphs, and extract database schemas from Neo4j.
- Manage Knowledge Graph Memory
- Store, update, and search memory entities and relationships as a knowledge graph, supporting long-term AI memory and context.
- Data Modeling & Visualization
- Define, validate, and visualize graph data models, including interactive schema design and import/export with tools like Arrows.
- Cloud Database Management
- Spin up, pause, resume, or delete Neo4j Aura cloud instances, manage tenants and projects, and automate infrastructure tasks from within your IDE.
- Secure, Bi-directional Integration
- Enable secure, persistent, and contextual connections between AI agents, developer tools, and Neo4j databases using standardized MCP protocol.
What is Neo4j MCP Server
AI agents can leverage Neo4j MCP Server to access, modify, and visualize complex graph data in real time, manage long-term memory as knowledge graphs, automate cloud database operations, and seamlessly integrate with the broader AI ecosystem. With standardized MCP interfaces, agents gain contextual access to data, tools, and infrastructure, accelerating development, improving AI reasoning, and enabling advanced use cases such as multi-modal retrieval, dynamic schema generation, and automated data insights.