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Cloudera Data Visualization MCP Server

Cloudera Data Visualization MCP Server

by kevintalbert
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

run_job

Trigger a rerun of scheduled jobs in Cloudera Data Visualization using job IDs or names to execute previously configured tasks again.

Instructions

Trigger a rerun of one or more CDV scheduled jobs. Provide exactly one of schedule_ids (comma-separated IDs) or schedule_names (comma-separated names).

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "run_job"
  }
}

Input Schema

NameRequiredDescriptionDefault
schedule_idsNo
schedule_namesNo

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 provided; description only states action 'trigger a rerun' without disclosing side effects, execution behavior (sync vs async), authentication needs, or output characteristics.

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?

Two sentences, front-loaded with purpose, second sentence provides parameter usage without any filler. Every sentence earns its place.

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?

Missing context on return value (output schema exists but not described), error cases, and prerequisites for using the tool. Incomplete for a job-triggering tool.

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

Parameters4/5

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

Despite 0% schema coverage, description explains parameter exclusivity (exactly one of schedule_ids or schedule_names) and clarifies that each is comma-separated, adding meaningful context beyond the schema.

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?

Description clearly states it triggers a rerun of CDV scheduled jobs, with specific verb 'trigger' and resource 'rerun of CDV scheduled jobs'. Among siblings, it is distinct from run_extract and others.

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 on when to use this tool versus alternatives like run_extract. Only parameter usage instruction is given, not when the tool is appropriate.

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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