{
  "markdown": "# Managed Service for Apache Kafka MCP Extension\n\nThe Managed Service for Apache Kafka MCP extension lets you manage Managed\nService for Apache Kafka clusters, as well as Kafka Connect clusters.\n\n-   You can create and manage Kafka clusters, including resources related to the\n    the cluster, such as topics, consumer groups, and ACLs.\n-   You can create and manage Connect clusters and connectors.\n\n## Why use the Managed Service for Apache Kafka MCP server?\n\nGoogle and Google Cloud\n[managed MCP servers](https://docs.cloud.google.com/mcp/overview) can be used in\nyour AI applications with enterprise-ready governance, security, and access\ncontrol.\n\n## Before you begin\n\n1.  In the Google Cloud console, on the\n    [project selector page](https://console.cloud.google.com/projectselector2/home/dashboard),\n    select or create a Google Cloud project.\n\n    > **Note**: If you don't plan to keep the resources that you create in this\n    > procedure, create a project instead of selecting an existing project.\n    > After you finish these steps, you can delete the project, removing all\n    > resources associated with the project.\n\n2.  Get your administrator to grant you the\n    [MCP Tool User role](https://docs.cloud.google.com/iam/docs/roles-permissions/mcp#mcp.toolUser)\n    (`roles/mcp.toolUser`) on the Google Cloud project. If you created a new\n    project, then you already have the required permissions.\n\n3.  Ensure your administrator has enabled the\n    [Managed Service for Apache Kafka API](https://console.cloud.google.com/marketplace/product/google/managedkafka.googleapis.com)\n    on the Google Cloud project.\n\n## Configure authentication\n\nThis extension uses Google Application Default Credentials (ADC) to perform\nauthentication. To login with ADC, run the following command in your terminal:\n\n```bash\ngcloud auth application-default login\n```\n\nFor additional details, see the\n[ADC documentation](https://docs.cloud.google.com/docs/authentication/application-default-credentials#personal).\n\n## Install the extension\n\nTo install the extension, run the following command in your terminal:\n\n```bash\ngemini extensions install https://github.com/gemini-cli-extensions/managed-kafka\n```\n\n## Available tools\n\nTo see a complete list of available tools and their schemas, see the\n[Managed Service for Apache Kafka MCP reference](https://docs.cloud.google.com/managed-service-for-apache-kafka/docs/reference/mcp).\n\n## Sample use cases\n\nThe following are sample use cases for the Managed Service for Apache Kafka MCP\nserver:\n\n-   Provision and scale streaming infrastructure. Create a Managed Service for\n    Apache Kafka cluster and dynamically adjust its compute resources (vCPU and\n    memory) to meet changing workload demands.\n-   Automate topic management. Provision Kafka topics with specific\n    configurations, partition counts and replication factors, to ensure high\n    availability and data durability.\n-   Build data pipelines with Kafka Connect: Deploy and manage Kafka Connect\n    clusters and connectors to integrate Kafka data with Google Cloud services\n    such as BigQuery or Pub/Sub.\n\n### Sample prompts\n\n-   Create a Kafka cluster named orders-cluster in us-central1 with 6 vCPUs and\n    12 GiB of memory, and add a topic called new-orders with 10 partitions and a\n    replication factor of 3.\n-   I need to scale up my telemetry-cluster to 15 vCPUs to handle an upcoming\n    traffic spike. Can you update the cluster configuration for me?\n-   Set up a BigQuery Sink connector in my Connect cluster analytics-connect\n    that streams data from the sensor-data topic into the streaming_analysis\n    dataset.\n\n## Optional security and safety configurations\n\nMCP introduces new security risks and considerations due to the wide variety of\nactions that you can take with MCP tools. To minimize and manage these risks,\nGoogle Cloud offers defaults and customizable policies to control the use of MCP\ntools in your Google Cloud organization or project.\n\nFor more information about MCP security and governance, see\n[AI security and safety](https://docs.cloud.google.com/mcp/ai-security-safety).\n\n## Quotas and limits\n\nThe Managed Service for Apache Kafka MCP server doesn't have its own quotas.\nThere is no limit on the number of call that can be made to the MCP server. You\nare still subject to the quotas enforced by the APIs called by the MCP server\ntools.\n\n## Reference and resources\n\n*   Explore the\n    [Managed Service for Apache Kafka remote MCP server reference documentation](https://docs.cloud.google.com/managed-service-for-apache-kafka/docs/reference/mcp),\n    which includes a list of all available tools, and the full input and output\n    schema for each tool.\n*   See the\n    [Managed Service for Apache Kafka overview](https://docs.cloud.google.com/managed-service-for-apache-kafka/docs).\n*   Learn about\n    [MCP security and governance](https://docs.cloud.google.com/mcp/ai-security-safety).\n",
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