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:
Clone the repository:
git clone <repository-url>
cd <repository-directory>
Create a virtual environment and activate it:
python -m venv venv
source venv/bin/activate # On Windows, use: venv\Scripts\activate
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 EventsTo 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 applicationkafka.py
: Kafka connector implementationserver.py
: MCP server implementation with tools for Kafka interactionsettings.py
: Configuration management using PydanticPublishes information to the configured Kafka topic.
consume information from the configured Kafka topic.
{
"mcpServers": {
"kafka": {
"env": {},
"args": [
"<PATH TO PROJECTS>/main.py"
],
"command": "python"
}
}
}
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