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Kafka Mcp Server
What is Kafka Mcp Server
kafka_mcp_server is a Message Context Protocol (MCP) server that integrates with Apache Kafka, enabling publish and consume functionalities for large language models (LLM) and agentic applications.
Use cases
Use cases for kafka_mcp_server include real-time data processing for AI applications, enabling communication between different AI models, and facilitating event-driven architectures in agentic applications.
How to use
To use kafka_mcp_server, clone the repository, set up a virtual environment, install the required dependencies, configure the .env file with Kafka settings, and run the server using the main.py script. You can also integrate it with Claude Desktop by adding the appropriate configuration.
Key features
Key features include the ability to publish messages to Kafka topics, consume messages from Kafka topics, and support for different transport options such as standard input/output and Server-Sent Events.
Where to use
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Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Overview
What is Kafka Mcp Server
kafka_mcp_server is a Message Context Protocol (MCP) server that integrates with Apache Kafka, enabling publish and consume functionalities for large language models (LLM) and agentic applications.
Use cases
Use cases for kafka_mcp_server include real-time data processing for AI applications, enabling communication between different AI models, and facilitating event-driven architectures in agentic applications.
How to use
To use kafka_mcp_server, clone the repository, set up a virtual environment, install the required dependencies, configure the .env file with Kafka settings, and run the server using the main.py script. You can also integrate it with Claude Desktop by adding the appropriate configuration.
Key features
Key features include the ability to publish messages to Kafka topics, consume messages from Kafka topics, and support for different transport options such as standard input/output and Server-Sent Events.
Where to use
undefined
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Content
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.txtIf 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
Create-Topic
Creates a new Kafka topic with specified parameters.
- Options:
--topicName of the topic to create--partitionsNumber of partitions to allocate--replication-factorReplication factor across brokers--config(optional) Topic-level configuration overrides (e.g.,retention.ms=604800000)
Delete-Topic
Deletes an existing Kafka topic.
- Options:
--topicName of the topic to delete--timeout(optional) Time to wait for deletion to complete
List-Topics
Lists all topics in the cluster (or filtered by pattern).
- Options:
--bootstrap-serverBroker address--pattern(optional) Regular expression to filter topic names--exclude-internal(optional) Exclude internal topics (default: true)
Topic-Configuration
Displays or alters configuration for one or more topics.
- Options:
--describeShow current configs for a topic--alterModify configs (e.g.,--add-config retention.ms=86400000,--delete-config cleanup.policy)--topicName of the topic
Topic-Metadata
Retrieves metadata about a topic or the cluster.
- Options:
--topic(If provided) Fetch metadata only for this topic--bootstrap-serverBroker address--include-offline(optional) Include brokers or partitions that are offline
Dev Tools Supporting MCP
The following are the main code editors that support the Model Context Protocol. Click the link to visit the official website for more information.










