Cloudera Data Visualization MCP Server

query_enhanced_data_api

Query Cloudera Data Visualization data via the Enhanced Data API, using legacy parameters or a JSON dataset request.

Instructions

Query data via the CDV Enhanced Data API (/api/data).

version: '0' for legacy API (provide dataset, limit, dimensions, aggregates), '1' for enhanced API (provide dsreq — a JSON-formatted dataset request string).

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": {
      "version": "<version>"
    },
    "name": "query_enhanced_data_api"
  }
}

Input Schema

Name	Required	Description	Default
`version`	Yes
`dataset`	No
`dsreq`	No
`limit`	No
`dimensions`	No
`aggregates`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0May 26, 2026

TDQS

B3.4/5.0

Behavior3/5

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

No annotations provided, so description carries full burden. It mentions API endpoint and version-dependent parameters but lacks disclosure of read-only nature, rate limits, authorization needs, or pagination behavior.

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?

Description is concise with two sentences and a bullet list for versions. No redundant information, but could be slightly more structured for readability.

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?

Output schema exists, so return values are covered. However, for a complex tool with 6 parameters and two versions, missing details on parameter semantics, behavioral traits, and sibling differentiation make the description incomplete.

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 coverage is 0%, so description must compensate. It maps version to parameter groups but provides no details on parameter format, constraints, or valid values (e.g., dsreq as JSON string). Adds marginal value beyond schema.

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?

Description clearly states it queries data via the CDV Enhanced Data API and explains version-based differences. However, it does not differentiate from the sibling tool 'query_dataapi', which likely has similar purpose.

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

Usage Guidelines3/5

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

Implied usage based on version choice (legacy vs enhanced), but no explicit guidance on when to use this tool versus alternatives like 'query_dataapi' or when not to use it.

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

Deploy Server