Power Automate via FlowStudio MCP This skill lets AI agents read, monitor, and operate Microsoft Power Automate cloud flows programmatically through a FlowStudio MCP server — no browser, no UI, no manual steps. Requires: A FlowStudio MCP subscription (or compatible Power Automate MCP server). You will need: MCP endpoint: https://mcp.flowstudio.app/mcp (same for all subscribers) API key / JWT token ( x-api-key header — NOT Bearer) Power Platform environment name (e.g. Default- ) Source of Truth Priority Source Covers 1 Real API response Always trust what the server actually returns 2 tools/list Tool names, parameter names, types, required flags 3 SKILL docs & reference files Response shapes, behavioral notes, workflow recipes Start every new session with tools/list . It returns the authoritative, up-to-date schema for every tool — parameter names, types, and required flags. The SKILL docs cover what tools/list cannot tell you: response shapes, non-obvious behaviors, and end-to-end workflow patterns. If any documentation disagrees with tools/list or a real API response, the API wins. Recommended Language: Python or Node.js All examples in this skill and the companion build / debug skills use Python with urllib.request (stdlib — no pip install needed). Node.js is an equally valid choice: fetch is built-in from Node 18+, JSON handling is native, and the async/await model maps cleanly onto the request-response pattern of MCP tool calls — making it a natural fit for teams already working in a JavaScript/TypeScript stack. Language Verdict Notes Python ✅ Recommended Clean JSON handling, no escaping issues, all skill examples use it Node.js (≥ 18) ✅ Recommended Native fetch + JSON.stringify / JSON.parse ; async/await fits MCP call patterns well; no extra packages needed PowerShell ⚠️ Avoid for flow operations ConvertTo-Json -Depth silently truncates nested definitions; quoting and escaping break complex payloads. Acceptable for a quick tools/list discovery call but not for building or updating flows. cURL / Bash ⚠️ Possible but fragile Shell-escaping nested JSON is error-prone; no native JSON parser TL;DR — use the Core MCP Helper (Python or Node.js) below. Both handle JSON-RPC framing, auth, and response parsing in a single reusable function. What You Can Do FlowStudio MCP has two access tiers. FlowStudio for Teams subscribers get both the fast Azure-table store (cached snapshot data + governance metadata) and full live Power Automate API access. MCP-only subscribers get the live tools — more than enough to build, debug, and operate flows. Live Tools — Available to All MCP Subscribers Tool What it does list_live_flows List flows in an environment directly from the PA API (always current) list_live_environments List all Power Platform environments visible to the service account list_live_connections List all connections in an environment from the PA API get_live_flow Fetch the complete flow definition (triggers, actions, parameters) get_live_flow_http_schema Inspect the JSON body schema and response schemas of an HTTP-triggered flow get_live_flow_trigger_url Get the current signed callback URL for an HTTP-triggered flow trigger_live_flow POST to an HTTP-triggered flow's callback URL (AAD auth handled automatically) update_live_flow Create a new flow or patch an existing definition in one call add_live_flow_to_solution Migrate a non-solution flow into a solution get_live_flow_runs List recent run history with status, start/end times, and errors get_live_flow_run_error Get structured error details (per-action) for a failed run get_live_flow_run_action_outputs Inspect inputs/outputs of any action (or every foreach iteration) in a run resubmit_live_flow_run Re-run a failed or cancelled run using its original trigger payload cancel_live_flow_run Cancel a currently running flow execution Store Tools — FlowStudio for Teams Subscribers Only These tools read from (and write to) the FlowStudio Azure table — a monitored snapshot of your tenant's flows enriched with governance metadata and run statistics. Tool What it does list_store_flows Search flows from the cache with governance flags, run failure rates, and owner metadata get_store_flow Get full cached details for a single flow including run stats and governance fields get_store_flow_trigger_url Get the trigger URL from the cache (instant, no PA API call) get_store_flow_runs Cached run history for the last N days with duration and remediation hints get_store_flow_errors Cached failed-only runs with failed action names and remediation hints get_store_flow_summary Aggregated stats: success rate, failure count, avg/max duration set_store_flow_state Start or stop a flow via the PA API and sync the result back to the store update_store_flow Update governance metadata (description, tags, monitor flag, notification rules, business impact) list_store_environments List all environments from the cache list_store_makers List all makers (citizen developers) from the cache get_store_maker Get a maker's flow/app counts and account status list_store_power_apps List all Power Apps canvas apps from the cache list_store_connections List all Power Platform connections from the cache Which Tool Tier to Call First Task Tool Notes List flows list_live_flows Always current — calls PA API directly Read a definition get_live_flow Always fetched live — not cached Debug a failure get_live_flow_runs → get_live_flow_run_error Use live run data ⚠️ list_live_flows returns a wrapper object with a flows array — access via result["flows"] . Store tools ( list_store_flows , get_store_flow , etc.) are available to FlowStudio for Teams subscribers and provide cached governance metadata. Use live tools when in doubt — they work for all subscription tiers. Step 0 — Discover Available Tools Always start by calling tools/list to confirm the server is reachable and see exactly which tool names are available (names may vary by server version): import json , urllib . request TOKEN = "" MCP = "https://mcp.flowstudio.app/mcp" def mcp_raw ( method , params = None , cid = 1 ) : payload = { "jsonrpc" : "2.0" , "method" : method , "id" : cid } if params : payload [ "params" ] = params req = urllib . request . Request ( MCP , data = json . dumps ( payload ) . encode ( ) , headers = { "x-api-key" : TOKEN , "Content-Type" : "application/json" , "User-Agent" : "FlowStudio-MCP/1.0" } ) try : resp = urllib . request . urlopen ( req , timeout = 30 ) except urllib . error . HTTPError as e : raise RuntimeError ( f"MCP HTTP { e . code } — check token and endpoint" ) from e return json . loads ( resp . read ( ) ) raw = mcp_raw ( "tools/list" ) if "error" in raw : print ( "ERROR:" , raw [ "error" ] ) ; raise SystemExit ( 1 ) for t in raw [ "result" ] [ "tools" ] : print ( t [ "name" ] , "—" , t [ "description" ] [ : 60 ] ) Core MCP Helper (Python) Use this helper throughout all subsequent operations: import json , urllib . request TOKEN = "" MCP = "https://mcp.flowstudio.app/mcp" def mcp ( tool , args , cid = 1 ) : payload = { "jsonrpc" : "2.0" , "method" : "tools/call" , "id" : cid , "params" : { "name" : tool , "arguments" : args } } req = urllib . request . Request ( MCP , data = json . dumps ( payload ) . encode ( ) , headers = { "x-api-key" : TOKEN , "Content-Type" : "application/json" , "User-Agent" : "FlowStudio-MCP/1.0" } ) try : resp = urllib . request . urlopen ( req , timeout = 120 ) except urllib . error . HTTPError as e : body = e . read ( ) . decode ( "utf-8" , errors = "replace" ) raise RuntimeError ( f"MCP HTTP { e . code } : { body [ : 200] } " ) from e raw = json . loads ( resp . read ( ) ) if "error" in raw : raise RuntimeError ( f"MCP error: { json . dumps ( raw [ 'error' ] ) } " ) text = raw [ "result" ] [ "content" ] [ 0 ] [ "text" ] return json . loads ( text ) Common auth errors: HTTP 401/403 → token is missing, expired, or malformed. Get a fresh JWT from mcp.flowstudio.app . HTTP 400 → malformed JSON-RPC payload. Check Content-Type: application/json and body structure. MCP error: {"code": -32602, ...} → wrong or missing tool arguments. Core MCP Helper (Node.js) Equivalent helper for Node.js 18+ (built-in fetch — no packages required): const TOKEN = "" ; const MCP = "https://mcp.flowstudio.app/mcp" ; async function mcp ( tool , args , cid = 1 ) { const payload = { jsonrpc : "2.0" , method : "tools/call" , id : cid , params : { name : tool , arguments : args } , } ; const res = await fetch ( MCP , { method : "POST" , headers : { "x-api-key" : TOKEN , "Content-Type" : "application/json" , "User-Agent" : "FlowStudio-MCP/1.0" , } , body : JSON . stringify ( payload ) , } ) ; if ( ! res . ok ) { const body = await res . text ( ) ; throw new Error ( MCP HTTP ${ res . status } : ${ body . slice ( 0 , 200 ) } ) ; } const raw = await res . json ( ) ; if ( raw . error ) throw new Error ( MCP error: ${ JSON . stringify ( raw . error ) } ) ; return JSON . parse ( raw . result . content [ 0 ] . text ) ; } Requires Node.js 18+. For older Node, replace fetch with https.request from the stdlib or install node-fetch . List Flows ENV = "Default-" result = mcp ( "list_live_flows" , { "environmentName" : ENV } )

Returns wrapper object:

{"mode": "owner", "flows": [{"id": "0757041a-...", "displayName": "My Flow",

"state": "Started", "triggerType": "Request", ...}], "totalCount": 42, "error": null}

for f in result [ "flows" ] : FLOW_ID = f [ "id" ]

plain UUID — use directly as flowName

print ( FLOW_ID , "|" , f [ "displayName" ] , "|" , f [ "state" ] ) Read a Flow Definition FLOW = "" flow = mcp ( "get_live_flow" , { "environmentName" : ENV , "flowName" : FLOW } )

Display name and state

print ( flow [ "properties" ] [ "displayName" ] ) print ( flow [ "properties" ] [ "state" ] )

List all action names

actions

flow [ "properties" ] [ "definition" ] [ "actions" ] print ( "Actions:" , list ( actions . keys ( ) ) )

Inspect one action's expression

print ( actions [ "Compose_Filter" ] [ "inputs" ] ) Check Run History

Most recent runs (newest first)

runs

mcp ( "get_live_flow_runs" , { "environmentName" : ENV , "flowName" : FLOW , "top" : 5 } )

Returns direct array:

[{"name": "08584296068667933411438594643CU15",

"status": "Failed",

"startTime": "2026-02-25T06:13:38.6910688Z",

"endTime": "2026-02-25T06:15:24.1995008Z",

"triggerName": "manual",

"error": {"code": "ActionFailed", "message": "An action failed..."}},

{"name": "08584296028664130474944675379CU26",

"status": "Succeeded", "error": null, ...}]

for r in runs : print ( r [ "name" ] , r [ "status" ] )

Get the name of the first failed run

run_id

next ( ( r [ "name" ] for r in runs if r [ "status" ] == "Failed" ) , None ) Inspect an Action's Output run_id = runs [ 0 ] [ "name" ] out = mcp ( "get_live_flow_run_action_outputs" , { "environmentName" : ENV , "flowName" : FLOW , "runName" : run_id , "actionName" : "Get_Customer_Record"

exact action name from the definition

} ) print ( json . dumps ( out , indent = 2 ) ) Get a Run's Error err = mcp ( "get_live_flow_run_error" , { "environmentName" : ENV , "flowName" : FLOW , "runName" : run_id } )

Returns:

{"runName": "08584296068...",

"failedActions": [

{"actionName": "HTTP_find_AD_User_by_Name", "status": "Failed",

"code": "NotSpecified", "startTime": "...", "endTime": "..."},

{"actionName": "Scope_prepare_workers", "status": "Failed",

"error": {"code": "ActionFailed", "message": "An action failed..."}}

],

"allActions": [

{"actionName": "Apply_to_each", "status": "Skipped"},

{"actionName": "Compose_WeekEnd", "status": "Succeeded"},

...

]}

The ROOT cause is usually the deepest entry in failedActions:

root

err [ "failedActions" ] [ - 1 ] print ( f"Root failure: { root [ 'actionName' ] } → { root [ 'code' ] } " ) Resubmit a Run result = mcp ( "resubmit_live_flow_run" , { "environmentName" : ENV , "flowName" : FLOW , "runName" : run_id } ) print ( result )

{"resubmitted": true, "triggerName": "..."}

Cancel a Running Run mcp ( "cancel_live_flow_run" , { "environmentName" : ENV , "flowName" : FLOW , "runName" : run_id } ) ⚠️ Do NOT cancel a run that shows Running because it is waiting for an adaptive card response. That status is normal — the flow is paused waiting for a human to respond in Teams. Cancelling it will discard the pending card. Full Round-Trip Example — Debug and Fix a Failing Flow

── 1. Find the flow ─────────────────────────────────────────────────────

result

mcp ( "list_live_flows" , { "environmentName" : ENV } ) target = next ( f for f in result [ "flows" ] if "My Flow Name" in f [ "displayName" ] ) FLOW_ID = target [ "id" ]

── 2. Get the most recent failed run ────────────────────────────────────

runs

mcp ( "get_live_flow_runs" , { "environmentName" : ENV , "flowName" : FLOW_ID , "top" : 5 } )

[{"name": "08584296068...", "status": "Failed", ...}, ...]

RUN_ID

next ( r [ "name" ] for r in runs if r [ "status" ] == "Failed" )

── 3. Get per-action failure breakdown ──────────────────────────────────

err

mcp ( "get_live_flow_run_error" , { "environmentName" : ENV , "flowName" : FLOW_ID , "runName" : RUN_ID } )

{"failedActions": [{"actionName": "HTTP_find_AD_User_by_Name", "code": "NotSpecified",...}], ...}

root_action

err [ "failedActions" ] [ - 1 ] [ "actionName" ] print ( f"Root failure: { root_action } " )

── 4. Read the definition and inspect the failing action's expression ───

defn

mcp ( "get_live_flow" , { "environmentName" : ENV , "flowName" : FLOW_ID } ) acts = defn [ "properties" ] [ "definition" ] [ "actions" ] print ( "Failing action inputs:" , acts [ root_action ] [ "inputs" ] )

── 5. Inspect the prior action's output to find the null ────────────────

out

mcp ( "get_live_flow_run_action_outputs" , { "environmentName" : ENV , "flowName" : FLOW_ID , "runName" : RUN_ID , "actionName" : "Compose_Names" } ) nulls = [ x for x in out . get ( "body" , [ ] ) if x . get ( "Name" ) is None ] print ( f" { len ( nulls ) } records with null Name" )

── 6. Apply the fix ─────────────────────────────────────────────────────

acts [ root_action ] [ "inputs" ] [ "parameters" ] [ "searchName" ] = \ "@coalesce(item()?['Name'], '')" conn_refs = defn [ "properties" ] [ "connectionReferences" ] result = mcp ( "update_live_flow" , { "environmentName" : ENV , "flowName" : FLOW_ID , "definition" : defn [ "properties" ] [ "definition" ] , "connectionReferences" : conn_refs } ) assert result . get ( "error" ) is None , f"Deploy failed: { result [ 'error' ] } "

⚠️ error key is always present — only fail if it is NOT None

── 7. Resubmit and verify ───────────────────────────────────────────────

mcp ( "resubmit_live_flow_run" , { "environmentName" : ENV , "flowName" : FLOW_ID , "runName" : RUN_ID } ) import time ; time . sleep ( 30 ) new_runs = mcp ( "get_live_flow_runs" , { "environmentName" : ENV , "flowName" : FLOW_ID , "top" : 1 } ) print ( new_runs [ 0 ] [ "status" ] )

Succeeded = done

Auth & Connection Notes Field Value Auth header x-api-key: — not Authorization: Bearer Token format Plain JWT — do not strip, alter, or prefix it Timeout Use ≥ 120 s for get_live_flow_run_action_outputs (large outputs) Environment name Default- (find it via list_live_environments or list_live_flows response) Reference Files MCP-BOOTSTRAP.md — endpoint, auth, request/response format (read this first) tool-reference.md — response shapes and behavioral notes (parameters are in tools/list ) action-types.md — Power Automate action type patterns connection-references.md — connector reference guide More Capabilities For diagnosing failing flows end-to-end → load the power-automate-debug skill. For building and deploying new flows → load the power-automate-build skill.