powerbi-orchestrator-mcp

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run_refresh

Trigger, monitor, and optionally wait for a Power BI dataset refresh; returns completion status, duration, and error details.

Instructions

Trigger, monitor, and optionally wait for a Power BI dataset refresh.

Use this tool when the user asks to:

Refresh data in a published Power BI semantic model.
Check the completion status of a refresh operation.
Perform full, automatic, or data-only refreshes.

Args: workspace_id: Fabric / Power BI workspace ID (UUID). dataset_id: Dataset / semantic model ID (UUID). refresh_type: "full", "automatic", "data_only", "calculate", or "clearValues". wait: Whether to poll and wait for the refresh to complete before returning. timeout_s: Maximum wait time in seconds (default: 1800). auth_mode: "interactive" or "service_principal". When omitted, PBI_AUTH_MODE is used, falling back to "interactive". tenant_id: Azure AD tenant ID. client_id: Azure AD client ID. dry_run: When True (default) no refresh is triggered and status is "DryRun". Pass dry_run=False to actually refresh.

Returns: Dict with refresh status, duration, error details, and rollback status if applicable.

Input Schema

Name	Required	Default
`wait`	No
`dry_run`	No
`auth_mode`	No
`client_id`	No
`tenant_id`	No
`timeout_s`	No
`dataset_id`	Yes
`refresh_type`	No	full
`workspace_id`	Yes

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Changed3 schema fields changedv1.23.0Oct 23, 2026
- addedInput schema / properties / auth_mode / anyOf
```
Added value: +[
+  {
+    "type": "string"
+  },
+  {
+    "type": "null"
+  }
+]
```
- changedInput schema / properties / auth_mode / default
```
Previous value: -"interactive"New value: +null
```
- removedInput schema / properties / auth_mode / type
```
Removed value: -"string"
```

Changed2 schema fields changedv1.18.0Oct 17, 2026

removedInput schema / properties / client_secret

Removed value: -{
-  "anyOf": [
-    {
-      "type": "string"
-    },
-    {
-      "type": "null"
-    }
-  ],
-  "default": null,
-  "title": "Client Secret"
-}

addedInput schema / properties / dry_run

Added value: +{
+  "default": true,
+  "title": "Dry Run",
+  "type": "boolean"
+}

First observedv0.1.0Sep 10, 2026

TDQS

A4.7/5.0

Behavior5/5

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

No annotations exist, so the description carries the full burden and does so well: it discloses that dry_run defaults to True and no refresh happens unless explicitly set False, that wait polls until completion with a timeout_s default of 1800, and that auth_mode resolves through PBI_AUTH_MODE to 'interactive'. That is exactly the safety and long-running-operation context an agent needs before invoking a mutation.

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 purpose sentence and the 'use when' list are front-loaded, and each Args entry earns its place given zero schema coverage. It is slightly long due to docstring-style formatting, and the Returns block is partly redundant with the existing output schema, but nothing is padded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 9-parameter mutation tool with no annotations, the description covers trigger semantics, polling behavior, auth resolution, the safe dry-run default, and return contents. Nothing an agent needs to call it correctly is missing.

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

Parameters5/5

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

Schema description coverage is 0%, and the description compensates for all nine parameters: UUID formats for workspace_id/dataset_id, the enumerated refresh_type values, the semantics of wait and timeout_s, the auth_mode fallback chain, and the critical dry_run default behavior. This adds substantial meaning the schema alone cannot convey.

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 opening sentence names a specific verb set (trigger, monitor, wait) and a specific resource (Power BI dataset refresh), which maps directly to a distinct capability none of the siblings (deploy_to_workspace, execute_dax_query, pre_deploy_check) cover. An agent can identify this tool's job without opening 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 Guidelines4/5

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

It gives an explicit 'Use this tool when the user asks to:' list covering refresh, status checks, and refresh type selection, which is clear positive routing. It does not state when NOT to use it or name an alternative for adjacent needs (e.g., health checks vs. actual refresh), so it stops short of a 5.

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