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mcp-fabric-api

mcp-fabric-api

by mkoziel2000
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

semantic_model_get_refresh_history

Read-only

Retrieve the refresh history of a semantic model to audit past refresh operations and troubleshoot failures.

Instructions

Get the refresh history of a semantic model via the Power BI API

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": {
      "workspaceId": "<workspaceId>",
      "semanticModelId": "<semanticModelId>"
    },
    "name": "semantic_model_get_refresh_history"
  }
}

Input Schema

NameRequiredDescriptionDefault
workspaceIdYesThe workspace ID (Power BI group ID)
semanticModelIdYesThe semantic model/dataset ID

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.8.0

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is known. The description adds only the context that this goes 'via the Power BI API' but does not disclose details such as pagination, history retention limits, or authentication requirements. It is consistent with annotations but adds limited behavioral value.

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?

One concise, front-loaded sentence with no filler. Every word adds information: the operation, the target resource, and the API context.

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?

For a simple read-only getter with two fully documented parameters and no optional inputs, the description is largely sufficient. The absence of an output schema means a bit more detail about the shape of the refresh history could help, but the tool's purpose and required IDs are clear enough for an agent to invoke it correctly.

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 100% and both parameters already have clear descriptions ('workspace ID (Power BI group ID)' and 'semantic model/dataset ID'). The description adds no extra parameter semantics, so the baseline of 3 applies.

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 uses a specific verb and resource ('Get ... refresh history of a semantic model') and clearly distinguishes this from sibling tools like semantic_model_get_details, semantic_model_get_datasources, and semantic_model_refresh. An agent can immediately tell what operation this performs without inspecting the schema.

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 gives no explicit guidance on when to call this tool instead of a sibling. It only implies use for inspecting past refreshes; there are no prerequisites, exclusion criteria, or pointers to alternatives such as semantic_model_get_details or dataflow_get_refresh_status.

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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