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Power Automate MCP Server by Flow Studio

List flow runs

get_live_flow_runs
Read-only

Fetch run history for a flow directly from Power Automate. Returns { runs, runCount, triggerChecks }: each run has name, status, startTime, endTime, trigger name/code, and any top-level error. IMPORTANT — no runs does NOT mean the flow is healthy. A trigger that fires and evaluates to nothing, or fails to evaluate, records a TRIGGER CHECK and never becomes a run. When there are no runs (or when includeTriggerChecks is set) this tool also reports the trigger check history, so "nothing ran" can be told apart from "the trigger has been failing". Read triggerChecks.byStatus before concluding a flow is fine.

Input Schema

NameRequiredDescriptionDefault
topNoMax runs to return. Paginates automatically. Default 30.
statusNoOnly runs with this status, e.g. Failed.
flowNameYesName (ID) of the flow.
startedAfterNoISO date-time. Only runs and checks that started at or after it.
startedBeforeNoISO date-time. Only runs and checks that started before it.
environmentNameYesName of the Power Platform environment.
triggerCheckStatusNoOnly trigger checks with this status; reads the checks.
includeTriggerChecksNoAlso report trigger check history when runs DO exist. Checks are always reported when there are no runs. Costs two extra API calls.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changed
    • addedInput schema / properties / startedAfter
      Added value: +{
      +  "description": "ISO date-time. Only runs and checks that started at or after it.",
      +  "type": "string"
      +}
    • addedInput schema / properties / startedBefore
      Added value: +{
      +  "description": "ISO date-time. Only runs and checks that started before it.",
      +  "type": "string"
      +}
    • addedInput schema / properties / status
      Added value: +{
      +  "description": "Only runs with this status, e.g. Failed.",
      +  "enum": [
      +    "Succeeded",
      +    "Failed",
      +    "Cancelled",
      +    "Running"
      +  ],
      +  "type": "string"
      +}
    • addedInput schema / properties / triggerCheckStatus
      Added value: +{
      +  "description": "Only trigger checks with this status; reads the checks.",
      +  "enum": [
      +    "Succeeded",
      +    "Failed",
      +    "Skipped"
      +  ],
      +  "type": "string"
      +}
  2. Changed1 schema field changed
    • addedInput schema / properties / includeTriggerChecks
      Added value: +{
      +  "description": "Also report trigger check history when runs DO exist. Checks are always reported when there are no runs. Costs two extra API calls.",
      +  "type": "boolean"
      +}
  3. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already declare readOnly/no-destructive, but the description goes well beyond by disclosing the response envelope, the fact that a trigger firing with no output produces a TRIGGER CHECK rather than a run, and the cost of includeTriggerChecks ('two extra API calls'). That is exactly the non-obvious behavioral context an agent cannot get from structured fields.

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 return shape, then the critical caveat, then the takeaway. Dense but every sentence carries a distinct point; the capitalized IMPORTANT and the closing restatement of the 'nothing ran vs trigger failing' distinction are slightly redundant.

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?

With no output schema, the description still covers the returned fields, the trigger-check edge case, and the cost tradeoff of an optional parameter — enough for an agent to call it correctly and interpret the result without guessing.

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

Parameters4/5

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

Schema coverage is 100%, so baseline is 3, but the description adds real meaning for includeTriggerChecks (checks are always reported when there are no runs, and the flag only matters when runs DO exist) and clarifies that time bounds apply to checks as well as runs. It says nothing about top/pagination semantics beyond the schema, keeping it from a 5.

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?

States a specific verb and resource ('fetch run history for a flow directly from Power Automate') and immediately enumerates the return shape (runs, runCount, triggerChecks). The 'live' / 'directly from Power Automate' framing implicitly separates it from the store_* siblings, so an agent can select it 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?

Gives explicit interpretive guidance: when there are no runs, or when includeTriggerChecks is set, trigger check history is reported, and the agent is told to read triggerChecks.byStatus before concluding a flow is healthy. It does not, however, name when to prefer it over siblings like get_live_flow_run_error or get_store_flow_runs, so routing between related diagnostic tools is still left to inference.

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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