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A suite of MCP servers enabling natural language interaction with Neo4j, including query generation, knowledge graph management, Aura cloud service control, and data modeling.
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A suite of MCP servers enabling natural language interaction with Neo4j, including query generation, knowledge graph management, Aura cloud service control, and data modeling.
The overall safety depends heavily on the specific server being used and its configuration. Read-only servers are generally safe, while those managing Aura instances or executing Cypher queries require careful access control and monitoring. Production deployments should prioritize secure configuration and consider the lack of formal support.
Performance will vary based on the complexity of the Cypher queries, the size of the knowledge graph, and the network latency. Consider optimizing queries and caching data to improve performance.
Cost considerations include Neo4j Aura usage, API call volume, and resource consumption. Optimize queries and manage instance sizes to minimize costs.
mcp-neo4j-cypherTranslates natural language into Cypher queries and executes them against a Neo4j database.
Executes arbitrary Cypher queries, potentially modifying or deleting data.
mcp-neo4j-memoryStores and retrieves entities and relationships in a Neo4j knowledge graph.
Allows writing and retrieval of knowledge graph data, potentially exposing sensitive information.
mcp-neo4j-cloud-aura-apiManages Neo4j Aura instances, including creation, deletion, and scaling.
Provides administrative access to Neo4j Aura cloud resources, enabling potentially destructive actions.
mcp-neo4j-data-modelingCreates, validates, and visualizes Neo4j graph data models.
Primarily a design and visualization tool with minimal risk of data modification.
Environment Variable
hybrid
The overall safety depends heavily on the specific server being used and its configuration. Read-only servers are generally safe, while those managing Aura instances or executing Cypher queries require careful access control and monitoring. Production deployments should prioritize secure configuration and consider the lack of formal support.
The level of autonomy depends on the specific server and the permissions granted to it. Exercise caution when using servers that can modify data or manage cloud resources.
Production Tip
Implement robust access control and monitoring to mitigate the risks associated with write operations and cloud resource management.
No, these servers are part of the Neo4j Labs program and are not officially supported.
STDIO, SSE, and HTTP are supported.
Use the `--transport http` flag and environment variables to configure host, port, and path.
The cloud deployment guide is located in README-Cloud.md.
Submit a Pull Request.
MIT License.
They are actively developed but lack SLAs or guarantees, so use caution in production.