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Kafka MCP Server

@MCP-Mirror

代码仓库

基本信息

分类

其他

许可证

Apache-2.0 license

传输方式

stdio

作者

MCP-Mirror

关于 Kafka MCP Server

Mirror of

#kafka#mcp-server#message-protocol

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": {
    "pavanjava_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, providing 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?

Install dependencies (pip install -r requirements.txt), configure a .env file with Kafka connection settings, then run python main.py --transport stdio. Supports stdio (default) and sse transports. Can be integrated with Claude Desktop via its MCP configuration.

Key features of Kafka MCP Server

  • Publish messages to a configured Kafka topic
  • Consume messages from a configured Kafka topic
  • Supports configurable Kafka bootstrap servers, topic name, and consumer group
  • Customizable tool descriptions via environment variables
  • Runs over stdio or SSE transports

Use cases of Kafka MCP Server

  • Enable an LLM to publish structured data to a Kafka topic
  • Allow an AI agent to consume and process messages from a Kafka stream
  • Integrate Kafka messaging into a Claude Desktop workflow

常见问题

1

What are the prerequisites?

Python 3.8+, a running Apache Kafka instance, and installation of dependencies `aiokafka`, `python-dotenv`, `pydantic-settings`, and `mcp-server`.

2

How do I configure the server?

Create a `.env` file in the project root with `KAFKA_BOOTSTRAP_SERVERS`, `TOPIC_NAME`, `IS_TOPIC_READ_FROM_BEGINNING`, and `DEFAULT_GROUP_ID_FOR_CONSUMER`. Optional `TOOL_PUBLISH_DESCRIPTION` and `TOOL_CONSUME_DESCRIPTION` can override tool descriptions.

3

What transport options are available?

The server supports `stdio` (standard input/output) and `sse` (Server-Sent Events). Use the `--transport` flag when running `main.py`.

4

Can I customize the tool names or descriptions?

Yes, by setting `TOOL_PUBLISH_DESCRIPTION` and `TOOL_CONSUME_DESCRIPTION` in the `.env` file you can provide custom descriptions for the publish and consume tools.

5

Are consumed messages re-readable?

No. Once a message is read from the topic it cannot be read again using the same consumer group. The server uses a configurable consumer group (`DEFAULT_GROUP_ID_FOR_CONSUMER`).

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