Kafka Dataops MCP

DataOps Kafka MCP server with consumer lag diagnosis and broker monitoring

Connector by Aguantar · GitHub account verified by the MCP Registry

IndexedMITLocal (stdio)

Chalk Labs

Need help deploying Kafka Dataops MCP?

Chalk Labs sets up agents like this inside real teams: connected to your tools, tested on your data, with a human in the loop where it matters.

Book a call

Install

Works with Claude Code, Codex, VS Code, Cursor, Windsurf, Claude Desktop. Read the repository before you give any tool access to your data.

npx agentmarket install connector/aguantar-kafka-dataops-mcp

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

Get the weekly diff

The weekly diff: one email a week with new agent tools, notable updates and grade changes, plus security alerts for tools you follow. Double opt-in, one-click unsubscribe.

About

DataOps Kafka MCP server with consumer lag diagnosis and broker monitoring

Reviews

Write a review

No reviews yet. Installed it? Reviews come from verified installers only. How reviews work

Permissions

What this server can do and what it asks for, from its tool list and install config. Checked Oct 25, 2026.

Tools: 4 read · 0 write · 0 deleteRead-only
Secrets: None asked for
Install scripts: Not scanned yet
Runs as: Python package

Tools by what they do 4

Read from the source code; the running server may list different tools.

Read 4 · Look things up without changing anything.

kafka_broker_status
kafka_consumer_lag
kafka_list_topics
kafka_topic_info

Secrets and settings it asks for

Other settings (environment variables or headers).

KAFKA_BOOTSTRAP_SERVERS

Tools (4)

Read from the source code; the running server may differ. Descriptions are the server’s own words; hidden characters are shown as [U+…].

kafka_broker_status
Check Kafka cluster health: brokers, controller, under-replicated partitions. Detects: - Missing brokers (expected 3 for this cluster) - ClusterIdMismatch pattern (Docker volume recreation issue) - Under-replicated partitions across all topics
kafka_consumer_lag
Monitor consumer group lag with operational diagnosis. Checks committed offsets vs log-end-offsets for each partition and generates diagnosis based on actual incident patterns: - Flink groups with "no active members" is NORMAL (checkpoint-based offset management) - Flink groups with no active members AND growing lag = likely Flink crash (matches 2026-02-21 incident: MySQL DELETE → tombstone → NPE → 50h outage) - Non-Flink groups with no active members = consuming application is down - Uneven lag distribution = possible hot partition or stuck consumer Args: group: Consumer group ID. Emp…
kafka_list_topics
List all Kafka topics with partition count, replication factor, and descriptions. Built-in descriptions for known topics (CDC pipeline, Circuit Connect). Args: include_internal: Include internal topics starting with '_' (default: False)
kafka_topic_info
Get topic details: partitions, replicas, ISR, configs, and health diagnosis. Checks replication health: - ISR < min.insync.replicas = writes FAILING (critical) - ISR < replication.factor but >= min.insync.replicas = degraded (warning) - Retention policy info (size-based deletion warnings) Args: topic: Topic name to inspect

Signals

Stars: 0
Forks: 0
Open issues: 0
Weekly downloads: 54
Last commit: Sep 30, 2026 (1 month ago)
Last release: Mar 19, 2026 (7 months ago)
Last package publish: Mar 19, 2026 (7 months ago)

From GitHub (fetched Oct 24, 2026) and the package registry.

Details

Registry name: io.github.Aguantar/kafka-dataops-mcp
Version: 0.1.0
Auth: No auth
Packages: pypi kafka-dataops-mcp
License: MIT
Repository: github.com/Aguantar/kafka-mcp-server
First seen: Oct 24, 2026
Last checked: Oct 25, 2026
Source: Official MCP Registry github-graphql

More from Aguantar

Done for you

Rather not set it up yourself?

Chalk Labs scopes, builds and runs agents for your team: the task audit, the eval harness, the integrations and the weekly ops report. Fixed scope, priced before we start.

See how we build AI agents →Read the case studies

Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.

launches shipped: 50+; launches shipped
media placements: 500+; media placements
founders on every account: 2; founders on every account

Press we've placed: Forbes · CoinDesk · Decrypt · Cointelegraph · The Block

Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.

Get Kafka Dataops MCP running in your business

Tell us what you want to automate. A founder replies within one working day with a plan, not a pitch deck.

Need help deploying Kafka Dataops MCP?

Call Get help

Cite this page

Kafka Dataops MCP. Agent Mart. https://agentmart.dev/connectors/aguantar-kafka-dataops-mcp (last updated 2026-10-25)