sap_analytics_cloud_mcp

sac_import_create_job

Create an import job for a SAP Analytics Cloud model, specifying import type, column mapping, and job settings to load data.

Instructions

Create import job for a model. Returns JobID/JobURL.

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_create_job"
  }
}

Input Schema

Name	Required	Description
`Mapping`	No	Column mapping: { source: target }
`modelId`	Yes	Model ID
`importType`	No	Import type
`JobSettings`	No	Job settings
`allowalteration`	No	Must be true to execute

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Jun 26, 2026

TDQS

C2.9/5.0

Behavior2/5

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

No annotations provided, so description must carry burden. It only states creation and return value. Does not disclose side effects, required permissions (e.g., allowalteration must be true), or async behavior. Minimal transparency.

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 concise with a single sentence. Front-loaded with action and result. Could include more context without being verbose.

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?

No output schema, but description mentions return value. Missing crucial context like the requirement that allowalteration must be true, or that jobs are typically asynchronous. Schema covers params fully, but overall context is insufficient for a complex 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?

Schema description coverage is 100%, so baseline is 3. The description adds no additional meaning beyond the schema; it does not explain parameter usage or constraints.

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 tool creates an import job for a model and returns a JobID/JobURL. However, it does not differentiate from sibling import creation tools like sac_import_create_currency_conversion_job or sac_import_create_public_dimension_job, which are more specific.

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 (e.g., sac_import_oneclick, sac_import_run_job). No prerequisites or context about the model or data source are mentioned.

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

Deploy Server