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kafka-mcp

MCP server for Apache Kafka that allows LLM agents to inspect topics, consumer groups, and safely manage offsets (reset, rewind).

glama
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Updated
Mar 8, 2026
Validated
Mar 10, 2026

Kafka MCP Server

Python License Kafka MCP


An MCP server implementation for Kafka, allowing LLMs to interact with and manage Kafka clusters.

Features

  • Cluster Management: View broker details describe_cluster, describe_brokers.
  • Topic Management: List list_topics, create create_topic, delete delete_topic, describe describe_topic, and increase partitions create_partitions.
  • Configuration Management: View describe_configs and modify alter_configs dynamic configs for topics, brokers, and groups.
  • Consumer Groups: List list_consumer_groups, describe describe_consumer_group, and securely manage offsets with reset_consumer_group_offset and rewind_consumer_group_offset_by_timestamp. Advanced tools include state validation, dry runs, and execution audit logging.
  • Messaging: Consume messages consume_messages (from beginning, latest, or specific offsets) and produce messages produce_message.

Prerequisites

  • Python 3.10+
  • uv package manager (recommended)
  • A running Kafka cluster (e.g., local Docker, Confluent Cloud, etc.)

Installation

  1. Clone the repository.
  2. Install dependencies:
    uv sync
    

Configuration

The server requires the KAFKA_BOOTSTRAP_SERVERS environment variable.

  • KAFKA_BOOTSTRAP_SERVERS: Comma-separated list of broker urls (e.g., localhost:9092).
  • KAFKA_CLIENT_ID: (Optional) Client ID for connection (default: kafka-mcp).

Usage

Running the Server

You can run the server directly using uv or python, or use Docker.

Using uv (Recommended)

export KAFKA_BOOTSTRAP_SERVERS=localhost:9092
uv run kafka-mcp

Using Docker

  1. Build the Docker image:

    docker build -t kafka-mcp .
    
  2. Run the container:

    docker run -i --rm -e KAFKA_BOOTSTRAP_SERVERS=host.docker.internal:9092 kafka-mcp
    

    (Note: Use host.docker.internal instead of localhost if your Kafka cluster is running on the host machine.)

Claude Desktop Configuration

Add the following to your Claude Desktop configuration file (claude_desktop_config.json):

{
  "mcpServers": {
    "kafka": {
      "command": "<uv PATH>",
      "args": [
        "--directory",
        "<kafka-mcp PATH>",
        "run",
        "kafka-mcp"
      ],
      "env": {
        "KAFKA_BOOTSTRAP_SERVERS": "localhost:9092"
      }
    }
  }
}

Debugging / Development

To verify that the server can start and connect to your Kafka cluster (ensure your Kafka is running first):

# Set your bootstrap server
export KAFKA_BOOTSTRAP_SERVERS=localhost:9092

# Run a quick check
uv run python -c "from src.kafka_mcp import main; print('Imports successful')"

Available Tools

CategoryTool NameDescription
Clusterdescribe_clusterGet cluster metadata (controller, brokers).
describe_brokersList all brokers.
Topicslist_topicsList all available topics.
describe_topicGet detailed info (partitions, replicas) for a topic.
create_topicCreate a new topic with partitions/replication factor.
delete_topicDelete a topic.
create_partitionsIncrease partitions for a topic.
Configsdescribe_configsView dynamic configs for topic/broker/group.
alter_configsUpdate dynamic configs.
Consumerslist_consumer_groupsList all active consumer groups.
describe_consumer_groupGet members and state of a group.
get_consumer_group_offsetsGet committed offset, high/low watermarks, and calculate total lag for a topic.
reset_consumer_group_offsetSafely change consumer group offsets to earliest, latest, or a specific offset.
rewind_consumer_group_offset_by_timestampRewind/advance consumer group offsets securely based on a timestamp.
Messagesconsume_messagesConsume messages from a topic (supports offsets, limits).
produce_messageSend a message to a topic.

Project Structure

src/kafka_mcp/
├── configs/       # Configuration handling
├── connections/   # Kafka client factories (singleton)
├── tools/         # Tool implementations
│   ├── admin.py     # Topic & Config management
│   ├── cluster.py   # Cluster metadata
│   ├── consumer.py  # Consumer group & message consumption
│   └── producer.py  # Message production
└── main.py        # Entry point & MCP tool registration

Troubleshooting

  • Connection Refused: Ensure KAFKA_BOOTSTRAP_SERVERS is correct and reachable.

TODO

  • SASL
  • JMX

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