Best for
- Developers on Neo4j Aura who want to manage instances through a conversational assistant
- Teams that need to quickly spin up or clean up test Aura instances
- Users already running Claude Desktop or another MCP client
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Neo4j Aura Manager MCP Server
Community
Manage Neo4j Aura cloud instances in natural language
GitHub source repository ↗
45FMRS · D
An instance-management MCP server for Neo4j Aura that lets an AI assistant create, look up, scale, and delete instances in natural language, with simple setup (STDIO plus two required secrets). It is maintained by the Neo4j Field GenAI team as a Labs project rather than an officially supported product, so it suits personal development and experimentation but not production-critical paths that need stability and support; pay particular attention to securing the highly privileged API credentials.
This is one of the MCP servers in the Neo4j Labs project, located in the repository subfolder servers/mcp-neo4j-cloud-aura-api, published on PyPI as mcp-neo4j-aura-manager, version 0.4.8. It connects to the Neo4j Aura console through the Aura API so that MCP-capable clients such as Claude Desktop, VS Code, Cursor, Windsurf, and Gemini CLI can manage Aura instances in natural language: create and destroy instances, find instances by name, scale them up and down, and enable features. It uses STDIO transport and requires the Aura API Client ID and Client Secret as environment variables, both of which are required secrets. It is an experimental Neo4j Labs project developed and maintained by the Neo4j Field GenAI team, is not supported by the Neo4j product team, and comes with no SLA or backwards compatibility guarantees; the official product MCP server lives in a separate repository, neo4j/mcp.
Setup
- Create API credentials in the Neo4j Aura console to obtain a Client ID and Client Secret. 2. Configure the server in your MCP client: run it with uvx mcp-neo4j-aura-manager (or launch the PyPI package mcp-neo4j-aura-manager 0.4.8) using stdio transport. 3. Set the NEO4J_AURA_CLIENT_ID and NEO4J_AURA_CLIENT_SECRET environment variables, and optionally NEO4J_NAMESPACE to namespace the tools. 4. Restart the client and confirm the server starts successfully.
Fit and risk
Not for
- Users looking for the officially supported Neo4j product MCP server (use neo4j/mcp)
- Production environments that require SLAs, backwards compatibility commitments, or a stable long-term API
- Users who do not use Neo4j Aura
Required permissions
- Neo4j Aura API credentials (Client ID and Client Secret) that can create, modify, and delete Aura instances
- Full administrative access to the user's Aura account
Risks and side effects
- The Aura API credentials are highly privileged; if leaked, another party could create, scale, or even delete instances, affecting billing and data availability
- The model may misinterpret natural language instructions, leading to accidental instance deletion or unexpected scaling costs
- As a Neo4j Labs experimental project, it may introduce breaking changes or deprecations with no compatibility guarantees
- An exposed Client Secret in logs or client configuration can leak credentials
Troubleshooting
- Verify that NEO4J_AURA_CLIENT_ID and NEO4J_AURA_CLIENT_SECRET are set correctly and have not expired
- Check that the client configuration uses the command and package mcp-neo4j-aura-manager version 0.4.8
- Review the server startup logs to confirm the STDIO connection has no errors
- If multiple Neo4j MCP servers cause tool name collisions, set NEO4J_NAMESPACE to differentiate them
- Confirm the credentials' Aura account has access to the target instances
Use cases
List the Aura instances in your account
Create a new instance with a given name, type, memory size, and features such as Graph Data Science
Find instances by name
Scale instances up or down
Delete instances that are no longer needed
Supported clients
Claude DesktopPartial support
VS CodePartial support
CursorPartial support
WindsurfPartial support
Gemini CLIPartial support