Aiven

What is Aiven MCP Server?

Aiven MCP Server is a Model Context Protocol (MCP) server that provides tools to interact with Aiven services. It allows AI agents to manage and query various Aiven services, including PostgreSQL, Kafka, ClickHouse, Valkey, and OpenSearch, as well as the broader Aiven ecosystem of native connectors. This enables developers to build full-stack solutions for a wide range of use cases.

How to use Aiven MCP Server?

To use the Aiven MCP Server, you need to configure it in an MCP-compatible application like Claude or Cursor. This involves setting up the server command and providing your Aiven API token and the repository directory as environment variables. The server is run using uv, a Python package installer and virtual environment manager.

Example Claude 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"
      }
    }
  }
}

Key Features

• Service Management: List projects and services within your Aiven account.
• Service Details: Get detailed information about specific services.
• Multi-Service Support: Interacts with a variety of Aiven-managed services.
• Open Source: The project is licensed under the Apache 2.0 license.

Use Cases

• Automated Infrastructure Management: Use an AI agent to programmatically list and manage your Aiven projects and services.
• Database Querying: Enable an AI agent to connect to and query your Aiven for PostgreSQL or ClickHouse databases.
• Data Streaming: Allow an AI agent to interact with Aiven for Kafka to manage topics and data streams.

FAQ from the project

As a developer-focused tool, common questions would likely revolve around:

• Authentication: How to create and configure the Aiven authentication token.
• Service-Specific Interactions: What are the specific capabilities for each supported Aiven service?
• Error Handling: How to troubleshoot connection issues or errors when interacting with the Aiven API.

For detailed setup and usage instructions, refer to the README.md file in the GitHub repository.

Aiven MCP Server

A Model Context Protocol (MCP) server for Aiven.

This provides access to the Aiven for PostgreSQL, Kafka, ClickHouse, Valkey and OpenSearch services running in Aiven and the wider Aiven ecosystem of native connectors. Enabling LLMs to build full stack solutions for all use-cases.

Features

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.

Configuration for Claude Desktop

1. Open the Claude Desktop configuration file located at:

   • On macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
   • On Windows: %APPDATA%/Claude/claude_desktop_config.json

2. Add the following:

{
  "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"
      }
    }
  }
}

Update the environment variables:

• $REPOSITORY_DIRECTORY to point to the folder cointaining the repository
• AIVEN_TOKEN to the Aiven login token.

3. Locate the command entry for uv and replace it with the absolute path to the uv executable. This ensures that the correct version of uv is used when starting the server. On a mac, you can find this path using which uv.

4. Restart Claude Desktop to apply the changes.

Configuration for Cursor

1. Navigate to Cursor -> Settings -> Cursor Settings

2. Select "MCP Servers"

3. Add a new server with

   • Name: mcp-aiven
   • Type: command
   • Command: uv --directory $REPOSITORY_DIRECTORY run --with-editable $REPOSITORY_DIRECTORY --python 3.13 mcp-aiven

Where $REPOSITORY_DIRECTORY is the path to the repository. You might need to add the AIVEN_BASE_URL, AIVEN_PROJECT_NAME and AIVEN_TOKEN as variables

Development

1. Add the following variables to a .env file in the root of the repository.

AIVEN_BASE_URL=https://api.aiven.io
AIVEN_TOKEN=$AIVEN_TOKEN

2. Run uv sync to install the dependencies. To install uv follow the instructions here. Then do source .venv/bin/activate.

3. For easy testing, you can run mcp dev mcp_aiven/mcp_server.py to start the MCP server.

Environment Variables

The following environment variables are used to configure the Aiven connection:

Required Variables

• AIVEN_BASE_URL: The Aiven API url
• AIVEN_TOKEN: The authentication token

Developer Considerations for Model Context Protocols (MCPs) and AI Agents

This section outlines key developer responsibilities and security considerations when working with Model Context Protocols (MCPs) and AI Agents within this system. Self-Managed MCPs:

• Customer Responsibility: MCPs are executed within the user's environment, not hosted by Aiven. Therefore, users are solely responsible for their operational management, security, and compliance, adhering to the shared responsibility model. (https://aiven.io/responsibility-matrix)
• Deployment and Maintenance: Developers must handle all aspects of MCP deployment, updates, and maintenance.

AI Agent Security:

• Permission Control: Access and capabilities of AI Agents are strictly governed by the permissions granted to the API token used for their authentication. Developers must meticulously manage these permissions.
• Credential Handling: Be acutely aware that AI Agents may require access credentials (e.g., database connection strings, streaming service tokens) to perform actions on your behalf. Exercise extreme caution when providing such credentials to AI Agents.
• Risk Assessment: Adhere to your organization's security policies and conduct thorough risk assessments before granting AI Agents access to sensitive resources.

API Token Best Practices:

• Principle of Least Privilege: Always adhere to the principle of least privilege. API tokens should be scoped and restricted to the minimum permissions necessary for their intended function.
• Token Management: Implement robust token management practices, including regular rotation and secure storage.

Key Takeaways:

• Users retain full control and responsibility for MCP execution and security.
• AI Agent permissions are directly tied to API token permissions.
• Exercise extreme caution when providing credentials to AI Agents.
• Strictly adhere to the principle of least privilege when managing API tokens.