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Glama
kinjal-1007

kafka-mcp

by kinjal-1007

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
list_topicsB

List all topics in the Kafka cluster.

describe_topicC

Describe a Kafka topic.

create_topicC

Create a new Kafka topic.

produce_messageC

Produce a message to a Kafka topic.

consume_messagesC

Consume messages from a Kafka topic.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

B3/5.0

Scored across 5 tools

Disambiguation4/5

Each tool targets a distinct Kafka resource action: listing, describing, creating topics, plus producing and consuming messages. The two message tools (produce_message, consume_messages) are clearly opposite operations, so little confusion. Minor overlap between list_topics and describe_topic could cause slight ambiguity but descriptions are clear enough.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern: list_topics, describe_topic, create_topic, produce_message, consume_messages. The naming convention is uniform with no mixture of styles or vague verbs.

Tool Count4/5

Five tools is a reasonable, well-scoped count for a Kafka server covering core topic management and messaging. It's on the leaner side but every tool earns its place for the apparent purpose.

Completeness3/5

The surface covers topic lifecycle (list, describe, create) and basic messaging (produce, consume). Missing obvious operations like delete_topic, update_topic (partitions/replication), and consumer group management, which are common Kafka workflows an agent would expect.

Maintenance

ActivityInactive
ResponsivenessNo issues