Kafka MCP
A natural language interface to manage Apache Kafka operations.
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'
संबंधित सर्वर
Scout Monitoring MCP
प्रायोजकPut performance and error data directly in the hands of your AI assistant.
Alpha Vantage MCP Server
प्रायोजकAccess financial market data: realtime & historical stock, ETF, options, forex, crypto, commodities, fundamentals, technical indicators, & more
Excalidraw MCP
Generate 25+ diagram types (flowchart, sequence, ER, mindmap, architecture, etc.) as Excalidraw files with natural language. CJK support, 30+ tech brand colors, Sugiyama auto-layout.
sep-mpc-server
A server for processing semantic embeddings, requiring external data files mounted via a Docker volume.
DeepInfra API
Provides a full suite of AI tools via DeepInfra’s OpenAI-compatible API, including image generation, text processing, embeddings, and speech recognition.
AST2LLM for Go
A local AST-powered context enhancement tool for LLMs that analyzes Go project structure for faster context resolution.
hanabi-cli
A terminal AI chat interface for any LLM model, with file context, MCP, and deployment support.
MCP HTTP Requests
A comprehensive HTTP client for API testing, web automation, and security testing with detailed logging.
browser-devtools-mcp
A Playwright-based MCP server that exposes a live browser as a traceable, inspectable, debuggable and controllable execution environment for AI agents.
JADX-AI-MCP
A JADX decompiler plugin that integrates with MCP to provide live reverse engineering support using LLMs.
Second Opinion
Review commits and codebases using external LLMs like OpenAI, Google Gemini, and Mistral.
App Market Intelligence MCP
Analyze app data from the Apple App Store and Google Play Store for market intelligence and insights.