Skip to main content
Glama
lensesio

Lenses MCP Server

by lensesio

get_topic_broker_configs

Retrieve Kafka broker configuration details for a specific topic to manage and optimize data streaming across clusters.

Instructions

Get broker configurations for a topic.

Args: environment: The environment name. topic_name: Name of the topic.

Returns: List of broker configuration details.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
environmentYes
topic_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The main handler function for the 'get_topic_broker_configs' tool. It is decorated with @mcp.tool() which handles registration. Makes a GET request to retrieve broker configurations for the specified topic.
    @mcp.tool()
    async def get_topic_broker_configs(environment: str, topic_name: str) -> List[Dict[str, Any]]:
        """
        Get broker configurations for a topic.
        
        Args:
            environment: The environment name.
            topic_name: Name of the topic.
        
        Returns:
            List of broker configuration details.
        """
        endpoint = f"/api/v1/environments/{environment}/proxy/api/topics/{topic_name}/brokerConfigs"
        return await api_client._make_request("GET", endpoint)
  • Calls register_topics(mcp) which defines and registers the get_topic_broker_configs tool among others.
    register_topics(mcp)
Behavior2/5

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

No annotations are provided, so the description carries full burden. It states this is a 'Get' operation, implying read-only behavior, but doesn't disclose any behavioral traits like authentication requirements, rate limits, error conditions, or what 'broker configurations' entail. For a tool with zero annotation coverage, this leaves significant gaps in understanding how it behaves.

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

Conciseness4/5

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

The description is appropriately sized with three sentences: purpose statement, parameter list, and return value. It's front-loaded with the core purpose. However, the Args and Returns sections use basic formatting without additional explanatory text, keeping it concise but slightly under-specified.

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

Completeness3/5

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

Given 2 parameters with 0% schema coverage and an output schema present, the description provides a basic purpose and parameter names but lacks details on parameter semantics, behavioral context, and differentiation from siblings. The output schema reduces the need to explain return values, but overall completeness is minimal for a tool with no annotations.

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

Parameters3/5

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

Schema description coverage is 0%, so the schema provides no parameter descriptions. The description adds minimal semantics by naming the parameters ('environment', 'topic_name') in the Args section, but doesn't explain what these mean (e.g., format of environment name, scope of topic_name). This partially compensates but falls short of fully clarifying parameter purposes.

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 clearly states the verb ('Get') and resource ('broker configurations for a topic'), making the purpose specific and understandable. However, it doesn't explicitly distinguish this tool from similar siblings like 'get_topic' or 'get_topic_metadata', which could also retrieve topic-related information.

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. With siblings like 'get_topic', 'get_topic_metadata', and 'get_topic_partitions', the description lacks any indication of when this specific broker configuration retrieval is appropriate, leaving usage context unclear.

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/lensesio/lenses-mcp'

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