Skip to main content
Glama
Aguantar

kafka-dataops-mcp

by Aguantar
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault

No arguments

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{
  "listChanged": false
}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
kafka_consumer_lagA

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. Empty = all groups.

kafka_topic_infoA

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

kafka_broker_statusA

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_list_topicsA

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)

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

Deploy Server
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

TDQS

A3.9/5.0

Scored across 4 tools

Disambiguation5/5

Each tool targets a distinct aspect of Kafka operation: cluster health, consumer lag, topic listing, and topic details. No functional overlap.

Naming Consistency4/5

All tools start with 'kafka_' but mix verb-noun ('list_topics') and noun phrases ('broker_status'). Still predictable and readable.

Tool Count4/5

Four tools is reasonable for a monitoring-focused server. Could expand with more actions but not too sparse.

Completeness3/5

Covers key diagnostic needs (health, lag, topic details) but lacks topic creation or consumer group management. Adequate for observability.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources