Kafka MCP Server
Enables AI agents to interact with Apache Kafka through natural language, supporting operations like producing/consuming messages, managing topics, and querying brokers, partitions, and consumer group offsets.
README
Kafka MCP
Overview
The Kafka MCP Server offers efficient way to convert prompts into actions into Kafka ecosystem. It is a natural language interface designed for agentic applications to efficiently manage Kafka operations and integrate seamlessly with MCP Clients enabling AI driven workflows to interact with processes in Kafka. Using this MCP Server, you can ask questions like:
- Publish message 'i am using kafka server' on the topic 'test-kafka'
- Consume the message from topic 'test-kafka'
- List all topics from the kafka environment
Features
- Natural Language Queries: Enables AI agents to query and update Redis using natural language.
- Seamless MCP Integration: Works with any MCP client for smooth communication.
- Full Kafka Support: Handles producer, consumer, topics, broker, partitions and offsets.
- Scalable & Lightweight: Designed for high-performance data operations.
Tools
This MCP Server offers various tools for Kafka:
consumer and producer tools allow to consumer and publish message on topics
topic tools allow to list, create, delete and describe topics in Kafka.
broker allows to get broker info.
partition tools allow to get partitions and partition offsets.
group_offset tools allow to get and reset offsets in Kafka.
Configurations
set the following in .env file or export manually
BOOTSTRAP_SERVERS=your_kafka_server
MCP_TRANSPORT=stdio
Local Development
Create a virtual environment
# Using venv (built-in)
python3 -m venv .venv
# Activate the virtual environment
# On Windows
.venv\Scripts\activate
# On macOS/Linux
source .venv/bin/activate
Install Dependencies
# Using pip
pip install -r requirements.txt
# Or using uv (faster)
uv pip install -r requirements.txt
Set Configurations in terminal/env
BOOTSTRAP_SERVERS=<your_kafka_url>
MCP_TRANSPORT=stdio
Run the application
python3 src/main.py
# OR
uv run python3 src/main.py
To interact with server,
Add the following configuration to your MCPO server's config.json file (e.g., in Claude Desktop):
{
"mcpServers": {
"kafka-mcp": {
"command": "python3",
"args": ["/Users/I528600/Desktop/mcp/kafka-mcp/src/main.py"],
"env": {
"BOOTSTRAP_SERVERS": "localhost:9092",
"MCP_TRANSPORT": "stdio"
}
}
}
}
Example prompts
- List all topics in the kafka cluster
- Create topic 'my-kafka' in kafka cluster
- Publish a message 'hello from mcp' to the topic 'my-kafka' in cluster
- Consume 2 messages from the topic 'my-kafka' in kafka cluster
- Describe the topic 'my-kafka'
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.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
E2B
Using MCP to run code via e2b.