strimzi-kafka-cli
Manage Apache Kafka on Kubernetes via Strimzi. Clusters, topics, users, connectors, MirrorMaker2, and node pools.
README
<!-- mcp-name: io.github.SystemCraftsman/strimzi-kafka-cli -->
Strimzi Kafka CLI
Strimzi Kafka CLI is a CLI that helps traditional Apache Kafka users -both developers and administrators- to easily adapt to Strimzi, a Kubernetes operator for Apache Kafka.
The main intention is to ramp up Strimzi usage by creating a similar CLI experience with the traditional Apache Kafka tools that mostly starts with kafka-* prefix under the bin directory in an ordinary Kafka package.
Strimzi Kafka CLI uses the kfk command as an abbreviation for "Kafka For Kubernetes" or simply "k a f k a" which reminds of the kafka-* prefix of the ordinary Kafka script file names.
While having similar set of commands or options for some of the common objects, Strimzi Kafka CLI has some extra capabilities for managing or configuring Strimzi related resources.
Following are the commands of the current version of Strimzi Kafka CLI, that are used for different purposes:
Usage: kfk [OPTIONS] COMMAND [ARGS]...
Strimzi Kafka CLI.
Options:
--version Show the version and exit.
--help Show this message and exit.
Commands:
acls Manages ACLs on Kafka.
clusters Creates, alters, deletes, describes Kafka cluster(s).
configs Adds/Removes entity config for a topic, client, user...
connect Manages Kafka Connect clusters, connectors, and MirrorMaker2.
clusters Creates, alters, deletes, describes KafkaConnect cluster(s).
connectors Creates, alters, deletes, describes KafkaConnector(s).
mirror-maker Lists, describes, creates, deletes KafkaMirrorMaker2(s).
console-consumer Reads data from Kafka topics and outputs it to...
console-producer Reads data from standard input and publish it to Kafka.
mcp Starts the Strimzi MCP server.
node-pools Lists, describes, creates, deletes KafkaNodePool(s).
operator Installs/Uninstalls Strimzi Kafka Operator.
topics Creates, alters, deletes, describes Kafka topic(s).
users Creates, alters, deletes, describes Kafka users(s).
Please take a look at the relevant article Strimzi Kafka CLI: Managing Strimzi in a Kafka Native Way for more details.
Installation
Using Python Package Installer
pip install strimzi-kafka-cli --user
Or to install Strimzi Kafka CLI in an isolated environment, you can simply use pipx:
pipx install strimzi-kafka-cli
To install with MCP server support:
pip install strimzi-kafka-cli[mcp] --user
Using Homebrew
#Tap the homebrew repository first.
brew tap systemcraftsman/strimzi-kafka-cli
#Install Strimzi Kafka CLI
brew install strimzi-kafka-cli
Installing the CLI by using Homebrew already uses a virtual environment, so you don't have to worry about your main Python environment.
Project requires: Python >=3.11
Examples
MCP Server
Strimzi Kafka CLI includes an MCP (Model Context Protocol) server that allows AI assistants to manage Strimzi Kafka deployments on Kubernetes.
Starting the MCP Server
kfk mcp
Registering with Claude Code
claude mcp add strimzi-kafka-cli -- kfk mcp
Available Tools (38)
| Category | Tools |
|---|---|
| Kafka Clusters | list_kafkas, get_kafka, get_kafka_status, create_kafka, delete_kafka, alter_kafka_config |
| Topics | list_topics, get_topic, create_topic, delete_topic, alter_topic |
| Users | list_users, get_user, create_user, delete_user, alter_user |
| Connect Clusters | list_connects, get_connect, create_connect, delete_connect, alter_connect |
| Connectors | list_connectors, get_connector, create_connector, delete_connector, alter_connector |
| MirrorMaker2 | list_mirror_maker_2s, get_mirror_maker_2, create_mirror_maker_2, delete_mirror_maker_2 |
| ACLs | add_or_remove_acls |
| Operator | install_operator, uninstall_operator |
| Node Pools | list_node_pools, get_node_pool, create_node_pool, delete_node_pool |
| Version | get_version |
Dependencies
Python Dependencies
Please see pyproject.toml file.
External Dependencies
Strimzi resources are automatically downloaded when the first kfk command is run. Strimzi Kafka CLI uses the Python Kubernetes client to interact with the cluster directly. You can check the dependency versions with:
kfk --version
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