Kafka MCP Server
Enables AI models to publish and consume messages from Apache Kafka topics through a standardized interface, making it easy to integrate Kafka messaging with LLM and agent applications.
pavanjava
README
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.
Overview
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
Prerequisites
- Python 3.8+
- Apache Kafka instance
- Python dependencies (see Installation section)
Installation
-
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
Configuration
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"
Usage
Running the Server
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
Integrating with Claude Desktop
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.
Project Structure
main.py
: Entry point for the applicationkafka.py
: Kafka connector implementationserver.py
: MCP server implementation with tools for Kafka interactionsettings.py
: Configuration management using Pydantic
Available Tools
kafka-publish
Publishes information to the configured Kafka topic.
kafka-consume
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
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
MCP Package Docs Server
Facilitates LLMs to efficiently access and fetch structured documentation for packages in Go, Python, and NPM, enhancing software development with multi-language support and performance optimization.
Claude Code MCP
An implementation of Claude Code as a Model Context Protocol server that enables using Claude's software engineering capabilities (code generation, editing, reviewing, and file operations) through the standardized MCP interface.
@kazuph/mcp-taskmanager
Model Context Protocol server for Task Management. This allows Claude Desktop (or any MCP client) to manage and execute tasks in a queue-based system.
Linear MCP Server
Enables interaction with Linear's API for managing issues, teams, and projects programmatically through the Model Context Protocol.
mermaid-mcp-server
A Model Context Protocol (MCP) server that converts Mermaid diagrams to PNG images.
Jira-Context-MCP
MCP server to provide Jira Tickets information to AI coding agents like Cursor

Linear MCP Server
A Model Context Protocol server that integrates with Linear's issue tracking system, allowing LLMs to create, update, search, and comment on Linear issues through natural language interactions.

Sequential Thinking MCP Server
This server facilitates structured problem-solving by breaking down complex issues into sequential steps, supporting revisions, and enabling multiple solution paths through full MCP integration.