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Cloudera Data Visualization MCP Server

Cloudera Data Visualization MCP Server

by kevintalbert
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_logger_level

Retrieve the current log level for a named logger to inspect logging configuration and diagnose issues.

Instructions

Retrieve the current log level for a specific logger by name.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "logger_name": "<logger_name>"
    },
    "name": "get_logger_level"
  }
}

Input Schema

NameRequiredDescriptionDefault
logger_nameYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
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 only says it retrieves a log level, but does not disclose side effects, permission requirements, or how errors (e.g., logger not found) are handled.

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?

A single, direct sentence with no fluff. Every word contributes to the purpose.

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

Completeness4/5

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

Given the tool is simple, has an output schema, and one parameter, the description is largely sufficient. It lacks only minor details like error handling, but completeness is good for a retrieval tool.

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?

The sole parameter 'logger_name' has no schema description (coverage 0%). The description adds 'by name', clarifying the parameter's role, but does not specify format, valid values, or behavior if the logger does not exist.

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

Purpose5/5

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

The description clearly states the action 'Retrieve', the resource 'current log level for a specific logger', and the method 'by name'. It effectively distinguishes from sibling tools like 'set_logger_level'.

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?

The description provides no guidance on when to use this tool versus alternatives like 'get_log_levels' or 'set_logger_level'. No context on prerequisites or typical scenarios.

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

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