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Power Automate MCP Server by Flow Studio

by io.github.ninihen1

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

TableJSON Schema
NameRequiredDescriptionDefault
topNoMax runs to return. Paginates automatically. Default 30.
flowNameYesName (ID) of the flow.
environmentNameYesName of the Power Platform environment.
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. Dates show when Glama detected each change.

  1. 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"
+}
  2. First observed

TDQS

A4.2/5.0
Behavior5/5

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

Annotations already mark the tool as read-only and non-destructive, so the description adds substantial value on top: it explains that a trigger can fire without creating a run, that trigger checks are reported when there are no runs, and that the agent must read triggerChecks.byStatus before concluding a flow is fine. This is exactly the kind of non-obvious behavioral disclosure that annotations cannot capture.

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 focused and front-loaded with the core action and return shape. The IMPORTANT caveat is long but earns its place because it prevents a common misinterpretation of the results. It is slightly redundant with the schema's includeTriggerChecks note but still well structured.

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 supplies the return object shape, per-run fields, trigger check semantics, and the key interpretation trap. Combined with complete schema parameter documentation and read-only annotations, an agent has enough information to call the tool correctly and interpret its results meaningfully.

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 the baseline is 3. The description does reinforce the meaning of includeTriggerChecks and explains the significance of triggerChecks in the response, but it does not add new parameter-level constraints or syntax beyond what the schema already states.

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 opens with a specific verb and resource: 'Fetch run history for a flow directly from Power Automate.' It also names the exact return shape ({ runs, runCount, triggerChecks }), which clearly distinguishes it from per-run detail tools like get_live_flow_run_error and from store-flow run tools like get_store_flow_runs.

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

Usage Guidelines3/5

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

The description provides excellent context about when trigger checks are included and warns that no runs does not mean the flow is healthy. However, it does not explicitly state when to use this tool versus siblings such as get_live_flow_run_error, get_live_flow_run_action_outputs, or get_store_flow_runs. Usage is implied rather than stated as a decision rule.

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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TDQS

A3.9/5.0
Disambiguation4/5

The consistent live/store prefixes and clear resource nouns make most tools distinguishable, and deprecated tools explicitly flag replacements. However, the duplicated live-vs-cache surfaces and multiple run/error-history tools can still require careful reading to choose correctly.

Naming Consistency5/5

All tools follow a consistent snake_case verb_noun pattern with stable qualifiers like live, store, flow, and run. Even meta-tools like list_skills and tool_search fit the same convention, and the few longer names such as add_live_flow_to_solution remain predictable.

Tool Count2/5

34 tools is well above the 25+ threshold for 'too many,' and the set is inflated by live/store duplication plus four deprecated tools scheduled for removal. Several tools could be consolidated or dropped without losing capability.

Completeness3/5

The server covers the main flow lifecycle well: list/get/create/update, state changes, running, resubmission, run diagnostics, environments, connections, and solution migration. Notable gaps include no delete flow, no remove-from-solution operation, and read-only connection management, which agents can partially work around.

Resources