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Kafka MCP Server

@pavanjava

代码仓库

基本信息

分类

其他

许可证

Apache-2.0

传输方式

stdio

作者

pavanjava

关于 Kafka MCP Server

暂无概览

Kafka MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

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

Kafka MCP Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

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

常见问题

1

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`).

2

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`.

3

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.

4

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.

5

Can a consumed message be read again?

No. The README notes that once a message is read from the topic using the same consumer group ID, it cannot be read again.

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