Skip to main content
Glama

produce_message

Produce messages to a Kafka topic by specifying topic name and value. Optionally include a key and headers for structured message delivery.

Instructions

Produces a message to a topic.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topic_nameYes
valueYes
keyNo
headersNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations exist, so the description must disclose behaviors. It only states the basic action without detailing side effects (e.g., auto-creation of topics, idempotency, retries) or requirements (e.g., authentication). For a producing tool, this is insufficient for safe invocation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence with no wasted words. It is front-loaded and immediately understandable. However, extreme brevity sacrifices completeness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (4 parameters, no schema descriptions, no annotations, has output schema), the description is severely incomplete. It lacks details on return values, error conditions, or messaging system specifics, which are critical for correct usage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description adds no meaning beyond parameter names. It does not explain the purpose of 'key' or 'headers' or how they affect message delivery. The agent must guess semantics from names alone, which is risky.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Produces a message to a topic.' clearly states the action (produce) and the resource (message to a topic). It distinguishes from sibling tools like 'consume_messages' or admin tools. However, the verb 'produces' is slightly vague; 'publish' or 'send' would be more standard.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives like 'consume_messages' or topic management tools. The description does not mention prerequisites, such as topic existence or authorization, leaving the agent without context for appropriate use.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/wklee610/kafka-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server