Kafka MCP Server

Name: Kafka MCP Server
Author: pavanjava

@pavanjava

リポジトリ

Kafka MCP Server について

概要はまだありません

基本情報

カテゴリ

その他

ライセンス

Apache-2.0

ランタイム

python

トランスポート

stdio

公開者

pavanjava

設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "kafka_mcp_server": {
      "command": "python",
      "args": [
        "-m",
        "venv",
        "venv"
      ]
    }
  }
}

ツール

ツールは検出されませんでした

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is Kafka MCP Server?

A Message Context Protocol (MCP) server that integrates with Apache Kafka to provide publish and consume functionalities for LLM and Agentic applications. It allows AI models to interact with Kafka topics through a standardized interface.

How to use Kafka MCP Server?

Set up Python 3.8+, an Apache Kafka instance, and install dependencies (aiokafka, python-dotenv, pydantic-settings, mcp-server). Create a .env file with Kafka configuration (bootstrap servers, topic name, etc.). Run the server via python main.py --transport stdio or --transport sse. Integrate with Claude Desktop by adding the server command to the MCP configuration JSON.

Key features of Kafka MCP Server

Publish messages to configured Kafka topics
Consume messages from Kafka topics
Create new Kafka topics with custom partitions and replication
Delete existing Kafka topics
List all topics or filter by pattern
Display or alter topic configurations
Retrieve topic metadata

Use cases of Kafka MCP Server

An AI agent publishing analysis results or alerts to a Kafka topic
An LLM consuming messages from a topic to generate summaries or responses
Programmatic topic lifecycle management (create, delete, list) via MCP tools
Modifying topic configuration (e.g., retention) without leaving the assistant interface
Inspecting cluster metadata to debug or monitor Kafka infrastructure

FAQ from Kafka MCP Server

What are the prerequisites for using Kafka MCP Server?

You need Python 3.8+, a running Apache Kafka instance, and the required Python packages (aiokafka, python-dotenv, pydantic-settings, mcp-server).

How do I configure Kafka connection settings?

Create a .env file in the project root with variables like KAFKA_BOOTSTRAP_SERVERS (default localhost:9092), TOPIC_NAME, and optionally IS_TOPIC_READ_FROM_BEGINNING and DEFAULT_GROUP_ID_FOR_CONSUMER.

Can I customize the tool descriptions shown to the LLM?

Yes. You can set optional environment variables TOOL_PUBLISH_DESCRIPTION and TOOL_CONSUME_DESCRIPTION in the .env file to override the default descriptions.

What transport options are available for running the server?

The server supports stdio (standard input/output) as the default transport and sse (Server-Sent Events) as an alternative, specified via the --transport argument.