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.

This project implements a server that allows AI models to interact with Kafka topics through a standardized interface. It supports:

• Publishing messages to Kafka topics
• Consuming messages from Kafka topics

• Python 3.8+
• Apache Kafka instance
• Python dependencies (see Installation section)

1. Clone the repository:

   git clone <repository-url>
   cd <repository-directory>

2. Create a virtual environment and activate it:

   python -m venv venv
   source venv/bin/activate  # On Windows, use: venv\Scripts\activate

3. Install the required dependencies:

   pip install -r requirements.txt

   If no requirements.txt exists, install the following packages:

   pip install aiokafka python-dotenv pydantic-settings mcp-server

Create a .env file in the project root with the following variables:

# Kafka Configuration
KAFKA_BOOTSTRAP_SERVERS=localhost:9092
TOPIC_NAME=your-topic-name
IS_TOPIC_READ_FROM_BEGINNING=False
DEFAULT_GROUP_ID_FOR_CONSUMER=kafka-mcp-group

# Optional: Custom Tool Descriptions
# TOOL_PUBLISH_DESCRIPTION="Custom description for the publish tool"
# TOOL_CONSUME_DESCRIPTION="Custom description for the consume tool"

You can run the server using the provided main.py script:

python main.py --transport stdio

Available transport options:

• stdio: Standard input/output (default)
• sse: Server-Sent Events

To use this Kafka MCP server with Claude Desktop, add the following configuration to your Claude Desktop configuration file:

{
    "mcpServers": {
        "kafka": {
            "command": "python",
            "args": [
                "<PATH TO PROJECTS>/main.py"
            ]
        }
    }
}

Replace <PATH TO PROJECTS> with the absolute path to your project directory.

• main.py: Entry point for the application
• kafka.py: Kafka connector implementation
• server.py: MCP server implementation with tools for Kafka interaction
• settings.py: Configuration management using Pydantic

Publishes information to the configured Kafka topic.

consume information from the configured Kafka topic.

• Note: once a message is read from the topic it can not be read again using the same groupid