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sap_analytics_cloud_mcp

sap_analytics_cloud_mcp

by JumenEngels
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

sac_import_get_model_metadata

Retrieve model dimension names, measure names, and field types to discover valid select fields before exporting fact data.

Instructions

Get model dimension names, measure names and field types. Call this BEFORE sac_export_get_fact_data_aggregation to discover valid $select fields (e.g. PD_O_BusinessUnit, SignedData). Required whenever field names are unknown. Use when: aggregating fact data, exporting by dimension, querying model structure.

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": {
      "modelId": "<modelId>"
    },
    "name": "sac_import_get_model_metadata"
  }
}

Input Schema

NameRequiredDescriptionDefault
modelIdYesModel ID

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior3/5

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

No annotations provided, so description must cover behavioral traits. It correctly implies it is a read-only operation (getting metadata) but does not explicitly state it's non-destructive, mention permissions, rate limits, or side effects. Adequate but minimal for a metadata retrieval tool.

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?

Front-loaded with the core purpose. The last sentence ('Use when...') is redundant but not overly verbose. Could be slightly more concise, but overall well-structured and efficient for a single-parameter tool.

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 no output schema and one required parameter, the description adequately covers what the tool returns and when to use it. Provides examples of returned fields. Lacks explanation of output format or error conditions, but sufficient for a simple metadata retrieval.

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?

Single parameter modelId with schema coverage 100%. Description adds no extra meaning beyond the schema's 'Model ID'. Baseline 3 is appropriate since schema covers the parameter fully, and no additional context is needed.

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?

Clearly states it gets model dimension names, measure names, and field types. Explicitly links to a specific sibling (sac_export_get_fact_data_aggregation), helping differentiate its purpose. Could be stronger by distinguishing from similar tools like sac_export_get_provider_metadata, but overall clear.

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

Usage Guidelines4/5

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

Explicitly states when to use: before sac_export_get_fact_data_aggregation to discover valid $select fields, and when field names are unknown. Lists three use cases. Does not mention when not to use or alternatives, but the guidance is concrete and actionable.

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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