flowstudio-power-automate-debug

name flowstudio-power-automate-debug description Debug failing Power Automate cloud flows using the FlowStudio MCP server. The Graph API only shows top-level status codes. This skill gives your agent action-level inputs and outputs to find the actual root cause. Load this skill when asked to: debug a flow, investigate a failed run, why is this flow failing, inspect action outputs, find the root cause of a flow error, fix a broken Power Automate flow, diagnose a timeout, trace a DynamicOperationRequestFailure, check connector auth errors, read error details from a run, or troubleshoot expression failures. Requires a FlowStudio MCP subscription — see https://mcp.flowstudio.app Power Automate Debugging with FlowStudio MCP A step-by-step diagnostic process for investigating failing Power Automate cloud flows through the FlowStudio MCP server. Real debugging examples : Expression error in child flow | Data entry, not a flow bug | Null value crashes child flow Prerequisite : A FlowStudio MCP server must be reachable with a valid JWT. See the flowstudio-power-automate-mcp skill for connection setup. Subscribe at https://mcp.flowstudio.app Source of Truth Always call list_skills / tool_search first to confirm available tool names and parameter schemas. Tool names and parameters may change between server versions. This skill covers response shapes, behavioral notes, and diagnostic patterns — things tool schemas cannot tell you. If this document disagrees with tool_search or a real API response, the API wins. Python Helper import json, urllib.request MCP_URL = "https://mcp.flowstudio.app/mcp" MCP_TOKEN = "<YOUR_JWT_TOKEN>" def mcp ( tool, **kwargs ): payload = json.dumps({ "jsonrpc" : "2.0" , "id" : 1 , "method" : "tools/call" , "params" : { "name" : tool, "arguments" : kwargs}}).encode() req = urllib.request.Request(MCP_URL, data=payload, headers={ "x-api-key" : MCP_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' ])} " ) return json.loads(raw[ "result" ][ "content" ][ 0 ][ "text" ]) ENV = "<environment-id>" # e.g. Default-xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx Step 1 — Locate the Flow result = mcp( "list_live_flows" , environmentName=ENV) # Returns a wrapper object: {mode, flows, totalCount, error} target = next (f for f in result[ "flows" ] if "My Flow Name" in f[ "displayName" ]) FLOW_ID = target[ "id" ] # plain UUID — use directly as flowName print (FLOW_ID) Step 2 — Find the Failing Run runs = mcp( "get_live_flow_runs" , environmentName=ENV, flowName=FLOW_ID, top= 5 ) # Returns direct array (newest first): # [{"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": "...", "status": "Succeeded", "error": null, ...}] for r in runs: print (r[ "name" ], r[ "status" ], r[ "startTime" ]) RUN_ID = next (r[ "name" ] for r in runs if r[ "status" ] == "Failed" ) Step 3 — Get the Top-Level Error CRITICAL : get_live_flow_run_error tells you which action failed. get_live_flow_run_action_outputs tells you why . You must call BOTH. Never stop at the error alone — error codes like ActionFailed , NotSpecified , and InternalServerError are generic wrappers. The actual root cause (wrong field, null value, HTTP 500 body, stack trace) is only visible in the action's inputs and outputs. err = mcp( "get_live_flow_run_error" , environmentName=ENV, flowName=FLOW_ID, runName=RUN_ID) # Returns: # { # "runName": "08584296068667933411438594643CU15", # "failedActions": [ # {"actionName": "Apply_to_each_prepare_workers", "status": "Failed", # "error": {"code": "ActionFailed", "message": "An action failed..."}, # "startTime": "...", "endTime": "..."}, # {"actionName": "HTTP_find_AD_User_by_Name", "status": "Failed", # "code": "NotSpecified", "startTime": "...", "endTime": "..."} # ], # "allActions": [ # {"actionName": "Apply_to_each", "status": "Skipped"}, # {"actionName": "Compose_WeekEnd", "status": "Succeeded"}, # ... # ] # } # failedActions is ordered outer-to-inner. The ROOT cause is the LAST entry: root = err[ "failedActions" ][- 1 ] print ( f"Root action: {root[ 'actionName' ]} → code: {root.get( 'code' )} " ) # allActions shows every action's status — useful for spotting what was Skipped # See common-errors.md to decode the error code. Step 4 — Inspect the Failing Action's Inputs and Outputs This is the most important step. get_live_flow_run_error only gives you a generic error code. The actual error detail — HTTP status codes, response bodies, stack traces, null values — lives in the action's runtime inputs and outputs. Always inspect the failing action immediately after identifying it. # Get the root failing action's full inputs and outputs root_action = err[ "failedActions" ][- 1 ][ "actionName" ] detail = mcp( "get_live_flow_run_action_outputs" , environmentName=ENV, flowName=FLOW_ID, runName=RUN_ID, actionName=root_action) if len (detail) > 1 : print ( f" {root_action} returned { len (detail)} repetitions; inspect iteration indexes" ) out = detail[ 0 ] if detail else {} print ( f"Action: {out.get( 'actionName' )} " ) print ( f"Status: {out.get( 'status' )} " ) # For HTTP actions, the real error is in outputs.body if isinstance (out.get( "outputs" ), dict ): status_code = out[ "outputs" ].get( "statusCode" ) body = out[ "outputs" ].get( "body" , {}) print ( f"HTTP {status_code} " ) print (json.dumps(body, indent= 2 )[: 500 ]) # Error bodies are often nested JSON strings — parse them if isinstance (body, dict ) and "error" in body: err_detail = body[ "error" ] if isinstance (err_detail, str ): err_detail = json.loads(err_detail) print ( f"Error: {err_detail.get( 'message' , err_detail)} " ) # For expression errors, the error is in the error field if out.get( "error" ): print ( f"Error: {out[ 'error' ]} " ) # Also check inputs — they show what expression/URL/body was used if out.get( "inputs" ): print ( f"Inputs: {json.dumps(out[ 'inputs' ], indent= 2 )[: 500 ]} " ) What the action outputs reveal (that error codes don't) Error code from get_live_flow_run_error What get_live_flow_run_action_outputs reveals ActionFailed Which nested action actually failed and its HTTP response NotSpecified The HTTP status code + response body with the real error InternalServerError The server's error message, stack trace, or API error JSON InvalidTemplate The exact expression that failed and the null/wrong-type value BadRequest The request body that was sent and why the server rejected it Foreach iterations When actionName refers to an action inside a foreach, the output tool can return every repetition of that action. Each item may include repetitionIndexes with the loop name and zero-based itemIndex . Use iterationIndex to inspect one iteration after you find the suspicious item: all_reps = mcp( "get_live_flow_run_action_outputs" , environmentName=ENV, flowName=FLOW_ID, runName=RUN_ID, actionName=root_action) for rep in all_reps[: 10 ]: print (rep.get( "repetitionIndexes" ), rep.get( "status" ), rep.get( "error" )) one_rep = mcp( "get_live_flow_run_action_outputs" , environmentName=ENV, flowName=FLOW_ID, runName=RUN_ID, actionName=root_action, iterationIndex= 3 ) Evidence Compose Bookends For uncertain connector work, add a Compose_*_Request before the risky action and a Compose_*_Result after it, with the result action allowed on both Succeeded and Failed . This gives future debugging a clean payload snapshot without requiring another deploy. Do not include secrets or long binary payloads in these bookends. Example: HTTP action returning 500 Error code: "InternalServerError" ← this tells you nothing Action outputs reveal: HTTP 500 body: {"error": "Cannot read properties of undefined (reading 'toLowerCase') at getClientParamsFromConnectionString (storage.js:20)"} ← THIS tells you the Azure Function crashed because a connection string is undefined Example: Expression error on null Error code: "BadRequest" ← generic Action outputs reveal: inputs: "body('HTTP_GetTokenFromStore')?['token']?['access_token']" outputs: "" ← empty string, the path resolved to null ← THIS tells you the response shape changed — token is at body.access_token, not body.token.access_token Step 5 — Read the Flow Definition defn = mcp( "get_live_flow" , environmentName=ENV, flowName=FLOW_ID) actions = defn[ "properties" ][ "definition" ][ "actions" ] print ( list (actions.keys())) Find the failing action in the definition. Inspect its inputs expression to understand what data it expects. Step 6 — Walk Back from the Failure When the failing action's inputs reference upstream actions, inspect those too. Walk backward through the chain until you find the source of the bad data: # Inspect multiple actions leading up to the failure for action_name in [root_action, "Compose_WeekEnd" , "HTTP_Get_Data" ]: result = mcp( "get_live_flow_run_action_outputs" , environmentName=ENV, flowName=FLOW_ID, runName=RUN_ID, actionName=action_name) out = result[ 0 ] if result else {} print ( f"\n--- {action_name} ( {out.get( 'status' )} ) ---" ) print ( f"Inputs: {json.dumps(out.get( 'inputs' , '' ), indent= 2 )[: 300 ]} " ) print ( f"Outputs: {json.dumps(out.get( 'outputs' , '' ), indent= 2 )[: 300 ]} " ) ⚠️ Output payloads from array-processing actions can be very large. Always slice (e.g. [:500] ) before printing. Tip : Omit actionName to list top-level actions when you're not sure which action produced the bad data. Once you pick an action inside a foreach, pass iterationIndex to avoid pulling every repetition into context. Step 7 — Pinpoint the Root Cause Expression Errors (e.g. split on null) If the error mentions InvalidTemplate or a function name: Find the action in the definition Check what upstream action/expression it reads Inspect that upstream action's output for null / missing fields # Example: action uses split(item()?['Name'], ' ') # → null Name in the source data result = mcp( "get_live_flow_run_action_outputs" , ..., actionName= "Compose_Names" ) if not result: print ( "No outputs returned for Compose_Names" ) names = [] else : names = result[ 0 ].get( "outputs" , {}).get( "body" ) or [] nulls = [x for x in names if x.get( "Name" ) is None ] print ( f" { len (nulls)} records with null Name" ) Wrong Field Path Expression triggerBody()?['fieldName'] returns null → fieldName is wrong. Inspect the trigger output to see the actual field names: result = mcp( "get_live_flow_run_action_outputs" , ..., actionName= "<trigger-action-name>" )