I craft unique cereal names, stories, and ridiculously cute Cereal Baby images.

pavanjava_kafka_mcp_server
Mirror ofhttps: //github.com/pavanjava/kafka_mcp_server
0
Github Watches
0
Github Forks
0
Github Stars
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 application -
kafka.py
: Kafka connector implementation -
server.py
: MCP server implementation with tools for Kafka interaction -
settings.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
相关推荐
I find academic articles and books for research and literature reviews.
Evaluator for marketplace product descriptions, checks for relevancy and keyword stuffing.
Confidential guide on numerology and astrology, based of GG33 Public information
Emulating Dr. Jordan B. Peterson's style in providing life advice and insights.
Advanced software engineer GPT that excels through nailing the basics.
Your go-to expert in the Rust ecosystem, specializing in precise code interpretation, up-to-date crate version checking, and in-depth source code analysis. I offer accurate, context-aware insights for all your Rust programming questions.
Converts Figma frames into front-end code for various mobile frameworks.
Entdecken Sie die umfassendste und aktuellste Sammlung von MCP-Servern auf dem Markt. Dieses Repository dient als zentraler Hub und bietet einen umfangreichen Katalog von Open-Source- und Proprietary MCP-Servern mit Funktionen, Dokumentationslinks und Mitwirkenden.
Die All-in-One-Desktop & Docker-AI-Anwendung mit integriertem Lappen, AI-Agenten, No-Code-Agent Builder, MCP-Kompatibilität und vielem mehr.
Fair-Code-Workflow-Automatisierungsplattform mit nativen KI-Funktionen. Kombinieren Sie visuelles Gebäude mit benutzerdefiniertem Code, SelbstHost oder Cloud, 400+ Integrationen.
🧑🚀 全世界最好的 llm 资料总结(数据处理、模型训练、模型部署、 O1 模型、 MCP 、小语言模型、视觉语言模型) | Zusammenfassung der weltbesten LLM -Ressourcen.
Reviews

user_rCzUAugn
I recently started using the pavanjava_kafka_mcp_server by MCP-Mirror and I must say, it has revolutionized my message queue management. The integration with Kafka is seamless, and the setup was straightforward thanks to the clear instructions. The GitHub repository provided all the necessary information. Highly recommend this server for anyone looking to streamline their processes! Check it out here: https://github.com/MCP-Mirror/pavanjava_kafka_mcp_server