kafka-dataops-mcp
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@kafka-dataops-mcpcheck consumer lag for group my-flink-app"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
kafka-dataops-mcp
mcp-name: io.github.Aguantar/kafka-dataops-mcp
A DataOps-focused Kafka MCP server with consumer lag diagnosis and broker health monitoring. Diagnosis logic is based on actual CDC pipeline operational experience.
Features
kafka_consumer_lag— Consumer group lag with incident-pattern diagnosiskafka_topic_info— Topic details with ISR/replication health checkskafka_broker_status— Cluster health: brokers, controller, under-replicated partitionskafka_list_topics— Topic catalog with built-in descriptions
Diagnosis based on real incidents
The diagnosis logic is not generic — it's based on actual operational experience:
Flink crash detection: "no active members" + growing lag = likely Flink Job failure (based on a 50-hour outage caused by MySQL DELETE → Debezium tombstone → Flink NPE)
Checkpoint vs consumer group: warns that Kafka consumer group reset alone is insufficient for Flink — checkpoints must be deleted first
ClusterIdMismatch: detects missing brokers and suggests Docker volume conflict as root cause
ISR monitoring: ISR < min.insync.replicas = write failures (critical)
Related MCP server: Kafka MCP Server
Installation
pip install kafka-dataops-mcpUsage with Claude Code
Add to your .mcp.json:
{
"mcpServers": {
"kafka": {
"command": "kafka-dataops-mcp",
"env": {
"KAFKA_BOOTSTRAP_SERVERS": "localhost:9092"
}
}
}
}Environment Variables
Variable | Default | Description |
|
| Kafka bootstrap servers |
|
| Command timeout in seconds |
License
MIT
Maintenance
Resources
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