Aiven MCP Server Integration

What does “Aiven” MCP Server do?

The Aiven MCP (Model Context Protocol) Server is a tool that connects AI assistants with the Aiven cloud platform, enabling seamless integration with Aiven’s managed services such as PostgreSQL, Kafka, ClickHouse, Valkey, and OpenSearch. By exposing these resources and functionalities through the MCP interface, the server empowers AI-driven workflows to perform tasks like listing projects, retrieving service details, and managing cloud infrastructure programmatically. This bridge between AI agents and Aiven’s ecosystem allows for enhanced development workflows, enabling automation, dynamic database management, and real-time service insights—all securely executed within the user’s environment.

List of Prompts

No prompt templates are mentioned in the repository.

List of Resources

No specific resources are described in the repository.

List of Tools

• list_projects
  List all projects on your Aiven account.
• list_services
  List all services in a specific Aiven project.
• get_service_details
  Get the detail of your service in a specific Aiven project.

Use Cases of this MCP Server

• Cloud Project Discovery and Management
  Developers can programmatically retrieve a list of all their Aiven projects, helping them manage and organize cloud resources more efficiently.
• Service Inventory Automation
  AI agents can automatically list all services running within a specific project, providing a real-time inventory for monitoring or auditing purposes.
• Detailed Service Insights
  Retrieve detailed information about individual services, supporting troubleshooting, compliance checks, and infrastructure documentation.
• Integration into AI Workflows
  The server can be used as a backend for AI assistants in developer tools, automating routine cloud tasks or surfacing relevant infrastructure data.
• Security and Compliance Monitoring
  By leveraging permission-based access, organizations can ensure that only authorized AI agents perform sensitive operations on cloud services.

How to set it up

Windsurf

No setup instructions found for Windsurf.

Claude

1. Open the Claude Desktop configuration file:
   • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
   • Windows: %APPDATA%/Claude/claude_desktop_config.json
2. Add the following configuration:

   {
     "mcpServers": {
       "mcp-aiven": {
         "command": "uv",
         "args": [
           "--directory",
           "$REPOSITORY_DIRECTORY",
           "run",
           "--with-editable",
           "$REPOSITORY_DIRECTORY",
           "--python",
           "3.13",
           "mcp-aiven"
         ],
         "env": {
           "AIVEN_BASE_URL": "https://api.aiven.io",
           "AIVEN_TOKEN": "$AIVEN_TOKEN"
         }
       }
     }
   }
   

3. Set $REPOSITORY_DIRECTORY to the path of the cloned repo and AIVEN_TOKEN to your Aiven login token.
4. Replace the uv command entry with the absolute path to the uv executable (find with which uv).
5. Restart Claude Desktop to apply changes.

Securing API Keys

Environment variables are used for sensitive information:

"env": {
  "AIVEN_BASE_URL": "https://api.aiven.io",
  "AIVEN_TOKEN": "$AIVEN_TOKEN"
}

Cursor

1. Open Cursor → Settings → Cursor Settings.
2. Select “MCP Servers.”
3. Add a new server:
   • Name: mcp-aiven
   • Type: command
   • Command:

     uv --directory $REPOSITORY_DIRECTORY run --with-editable $REPOSITORY_DIRECTORY --python 3.13 mcp-aiven
     

4. Set $REPOSITORY_DIRECTORY and add AIVEN_BASE_URL, AIVEN_PROJECT_NAME, and AIVEN_TOKEN as variables.

Cline

No setup instructions found for Cline.

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "MCP-name": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent can use this MCP as a tool with access to all its functions and capabilities. Remember to change “MCP-name” to “mcp-aiven” and update the URL accordingly.

Overview

Based on the above, the Aiven MCP Server provides clear tooling and secure setup, but lacks documentation for resources and prompt templates. It’s a solid, functional MCP server for Aiven-specific automation, earning a moderate score for its focus and clarity, but missing more advanced MCP features.

MCP Score

Roots and Sampling:
No evidence of support for Roots or Sampling in the repository documentation or code listings.