flowstudio-power-automate-build

仓库: github/awesome-copilot
安装量: 285
排名: #3167

安装

npx skills add https://github.com/github/awesome-copilot --skill flowstudio-power-automate-build
Build & Deploy Power Automate Flows with FlowStudio MCP
Step-by-step guide for constructing and deploying Power Automate cloud flows
programmatically through the FlowStudio MCP server.
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 tools/list first to confirm available tool names and their parameter schemas. Tool names and parameters may change between server versions. This skill covers response shapes, behavioral notes, and build patterns — things tools/list cannot tell you. If this document disagrees with tools/list or a real API response, the API wins. Python Helper import json , urllib . request MCP_URL = "https://mcp.flowstudio.app/mcp" MCP_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 = ""

e.g. Default-xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx

Step 1 — Safety Check: Does the Flow Already Exist? Always look before you build to avoid duplicates: results = mcp ( "list_store_flows" , environmentName = ENV , searchTerm = "My New Flow" )

list_store_flows returns a direct array (no wrapper object)

if len ( results )

0 :

Flow exists — modify rather than create

id format is "envId.flowId" — split to get the flow UUID

FLOW_ID

results
[
0
]
[
"id"
]
.
split
(
"."
,
1
)
[
1
]
print
(
f"Existing flow:
{
FLOW_ID
}
"
)
defn
=
mcp
(
"get_live_flow"
,
environmentName
=
ENV
,
flowName
=
FLOW_ID
)
else
:
print
(
"Flow not found — building from scratch"
)
FLOW_ID
=
None
Step 2 — Obtain Connection References
Every connector action needs a
connectionName
that points to a key in the
flow's
connectionReferences
map. That key links to an authenticated connection
in the environment.
MANDATORY
You MUST call list_live_connections first — do NOT ask the user for connection names or GUIDs. The API returns the exact values you need. Only prompt the user if the API confirms that required connections are missing. 2a — Always call list_live_connections first conns = mcp ( "list_live_connections" , environmentName = ENV )

Filter to connected (authenticated) connections only

active

[ c for c in conns [ "connections" ] if c [ "statuses" ] [ 0 ] [ "status" ] == "Connected" ]

Build a lookup: connectorName → connectionName (id)

conn_map

{ } for c in active : conn_map [ c [ "connectorName" ] ] = c [ "id" ] print ( f"Found { len ( active ) } active connections" ) print ( "Available connectors:" , list ( conn_map . keys ( ) ) ) 2b — Determine which connectors the flow needs Based on the flow you are building, identify which connectors are required. Common connector API names: Connector API name SharePoint shared_sharepointonline Outlook / Office 365 shared_office365 Teams shared_teams Approvals shared_approvals OneDrive for Business shared_onedriveforbusiness Excel Online (Business) shared_excelonlinebusiness Dataverse shared_commondataserviceforapps Microsoft Forms shared_microsoftforms Flows that need NO connections (e.g. Recurrence + Compose + HTTP only) can skip the rest of Step 2 — omit connectionReferences from the deploy call. 2c — If connections are missing, guide the user connectors_needed = [ "shared_sharepointonline" , "shared_office365" ]

adjust per flow

missing

[ c for c in connectors_needed if c not in conn_map ] if not missing : print ( "✅ All required connections are available — proceeding to build" ) else :

── STOP: connections must be created interactively ──

Connections require OAuth consent in a browser — no API can create them.

print ( "⚠️ The following connectors have no active connection in this environment:" ) for c in missing : friendly = c . replace ( "shared_" , "" ) . replace ( "onlinebusiness" , " Online (Business)" ) print ( f" • { friendly } (API name: { c } )" ) print ( ) print ( "Please create the missing connections:" ) print ( " 1. Open https://make.powerautomate.com/connections" ) print ( " 2. Select the correct environment from the top-right picker" ) print ( " 3. Click '+ New connection' for each missing connector listed above" ) print ( " 4. Sign in and authorize when prompted" ) print ( " 5. Tell me when done — I will re-check and continue building" )

DO NOT proceed to Step 3 until the user confirms.

After user confirms, re-run Step 2a to refresh conn_map.

2d — Build the connectionReferences block Only execute this after 2c confirms no missing connectors: connection_references = { } for connector in connectors_needed : connection_references [ connector ] = { "connectionName" : conn_map [ connector ] ,

the GUID from list_live_connections

"source"
:
"Invoker"
,
"id"
:
f"/providers/Microsoft.PowerApps/apis/
{
connector
}
"
}
IMPORTANT —
host.connectionName
in actions
When building actions in Step 3, set host.connectionName to the key from this map (e.g. shared_teams ), NOT the connection GUID. The GUID only goes inside the connectionReferences entry. The engine matches the action's host.connectionName to the key to find the right connection. Alternative — if you already have a flow using the same connectors, you can extract connectionReferences from its definition: ref_flow = mcp ( "get_live_flow" , environmentName = ENV , flowName = "" ) connection_references = ref_flow [ "properties" ] [ "connectionReferences" ] See the power-automate-mcp skill's connection-references.md reference for the full connection reference structure. Step 3 — Build the Flow Definition Construct the definition object. See flow-schema.md for the full schema and these action pattern references for copy-paste templates: action-patterns-core.md — Variables, control flow, expressions action-patterns-data.md — Array transforms, HTTP, parsing action-patterns-connectors.md — SharePoint, Outlook, Teams, Approvals definition = { "$schema" : "https://schema.management.azure.com/providers/Microsoft.Logic/schemas/2016-06-01/workflowdefinition.json#" , "contentVersion" : "1.0.0.0" , "triggers" : { . . . } ,

see trigger-types.md / build-patterns.md

"actions" : { . . . }

see ACTION-PATTERNS-*.md / build-patterns.md

} See build-patterns.md for complete, ready-to-use flow definitions covering Recurrence+SharePoint+Teams, HTTP triggers, and more. Step 4 — Deploy (Create or Update) update_live_flow handles both creation and updates in a single tool. Create a new flow (no existing flow) Omit flowName — the server generates a new GUID and creates via PUT: result = mcp ( "update_live_flow" , environmentName = ENV ,

flowName omitted → creates a new flow

definition

definition , connectionReferences = connection_references , displayName = "Overdue Invoice Notifications" , description = "Weekly SharePoint → Teams notification flow, built by agent" ) if result . get ( "error" ) is not None : print ( "Create failed:" , result [ "error" ] ) else :

Capture the new flow ID for subsequent steps

FLOW_ID

result [ "created" ] print ( f"✅ Flow created: { FLOW_ID } " ) Update an existing flow Provide flowName to PATCH: result = mcp ( "update_live_flow" , environmentName = ENV , flowName = FLOW_ID , definition = definition , connectionReferences = connection_references , displayName = "My Updated Flow" , description = "Updated by agent on " + import ( 'datetime' ) . datetime . utcnow ( ) . isoformat ( ) ) if result . get ( "error" ) is not None : print ( "Update failed:" , result [ "error" ] ) else : print ( "Update succeeded:" , result ) ⚠️ update_live_flow always returns an error key. null (Python None ) means success — do not treat the presence of the key as failure. ⚠️ description is required for both create and update. Common deployment errors Error message (contains) Cause Fix missing from connectionReferences An action's host.connectionName references a key that doesn't exist in the connectionReferences map Ensure host.connectionName uses the key from connectionReferences (e.g. shared_teams ), not the raw GUID ConnectionAuthorizationFailed / 403 The connection GUID belongs to another user or is not authorized Re-run Step 2a and use a connection owned by the current x-api-key user InvalidTemplate / InvalidDefinition Syntax error in the definition JSON Check runAfter chains, expression syntax, and action type spelling ConnectionNotConfigured A connector action exists but the connection GUID is invalid or expired Re-check list_live_connections for a fresh GUID Step 5 — Verify the Deployment check = mcp ( "get_live_flow" , environmentName = ENV , flowName = FLOW_ID )

Confirm state

print ( "State:" , check [ "properties" ] [ "state" ] )

Should be "Started"

Confirm the action we added is there

acts

check
[
"properties"
]
[
"definition"
]
[
"actions"
]
print
(
"Actions:"
,
list
(
acts
.
keys
(
)
)
)
Step 6 — Test the Flow
MANDATORY
Before triggering any test run, ask the user for confirmation . Running a flow has real side effects — it may send emails, post Teams messages, write to SharePoint, start approvals, or call external APIs. Explain what the flow will do and wait for explicit approval before calling trigger_live_flow or resubmit_live_flow_run . Updated flows (have prior runs) The fastest path — resubmit the most recent run: runs = mcp ( "get_live_flow_runs" , environmentName = ENV , flowName = FLOW_ID , top = 1 ) if runs : result = mcp ( "resubmit_live_flow_run" , environmentName = ENV , flowName = FLOW_ID , runName = runs [ 0 ] [ "name" ] ) print ( result ) Flows already using an HTTP trigger Fire directly with a test payload: schema = mcp ( "get_live_flow_http_schema" , environmentName = ENV , flowName = FLOW_ID ) print ( "Expected body:" , schema . get ( "triggerSchema" ) ) result = mcp ( "trigger_live_flow" , environmentName = ENV , flowName = FLOW_ID , body = { "name" : "Test" , "value" : 1 } ) print ( f"Status: { result [ 'status' ] } " ) Brand-new non-HTTP flows (Recurrence, connector triggers, etc.) A brand-new Recurrence or connector-triggered flow has no runs to resubmit and no HTTP endpoint to call. Deploy with a temporary HTTP trigger first, test the actions, then swap to the production trigger. 7a — Save the real trigger, deploy with a temporary HTTP trigger

Save the production trigger you built in Step 3

production_trigger

definition [ "triggers" ]

Replace with a temporary HTTP trigger

definition [ "triggers" ] = { "manual" : { "type" : "Request" , "kind" : "Http" , "inputs" : { "schema" : { } } } }

Deploy (create or update) with the temp trigger

result

mcp ( "update_live_flow" , environmentName = ENV , flowName = FLOW_ID ,

omit if creating new

definition

definition , connectionReferences = connection_references , displayName = "Overdue Invoice Notifications" , description = "Deployed with temp HTTP trigger for testing" ) if result . get ( "error" ) is not None : print ( "Deploy failed:" , result [ "error" ] ) else : if not FLOW_ID : FLOW_ID = result [ "created" ] print ( f"✅ Deployed with temp HTTP trigger: { FLOW_ID } " ) 7b — Fire the flow and check the result

Trigger the flow

test

mcp ( "trigger_live_flow" , environmentName = ENV , flowName = FLOW_ID ) print ( f"Trigger response status: { test [ 'status' ] } " )

Wait for the run to complete

import time ; time . sleep ( 15 )

Check the run result

runs

mcp ( "get_live_flow_runs" , environmentName = ENV , flowName = FLOW_ID , top = 1 ) run = runs [ 0 ] print ( f"Run { run [ 'name' ] } : { run [ 'status' ] } " ) if run [ "status" ] == "Failed" : err = mcp ( "get_live_flow_run_error" , environmentName = ENV , flowName = FLOW_ID , runName = run [ "name" ] ) root = err [ "failedActions" ] [ - 1 ] print ( f"Root cause: { root [ 'actionName' ] } → { root . get ( 'code' ) } " )

Debug and fix the definition before proceeding

See power-automate-debug skill for full diagnosis workflow

7c — Swap to the production trigger Once the test run succeeds, replace the temporary HTTP trigger with the real one:

Restore the production trigger

definition
[
"triggers"
]
=
production_trigger
result
=
mcp
(
"update_live_flow"
,
environmentName
=
ENV
,
flowName
=
FLOW_ID
,
definition
=
definition
,
connectionReferences
=
connection_references
,
description
=
"Swapped to production trigger after successful test"
)
if
result
.
get
(
"error"
)
is
not
None
:
print
(
"Trigger swap failed:"
,
result
[
"error"
]
)
else
:
print
(
"✅ Production trigger deployed — flow is live"
)
Why this works
The trigger is just the entry point — the actions are
identical regardless of how the flow starts. Testing via HTTP trigger
exercises all the same Compose, SharePoint, Teams, etc. actions.
Connector triggers
(e.g. "When an item is created in SharePoint"):
If actions reference
triggerBody()
or
triggerOutputs()
, pass a
representative test payload in
trigger_live_flow
's
body
parameter
that matches the shape the connector trigger would produce.
Gotchas
Mistake
Consequence
Prevention
Missing
connectionReferences
in deploy
400 "Supply connectionReferences"
Always call
list_live_connections
first
"operationOptions"
missing on Foreach
Parallel execution, race conditions on writes
Always add
"Sequential"
union(old_data, new_data)
Old values override new (first-wins)
Use
union(new_data, old_data)
split()
on potentially-null string
InvalidTemplate
crash
Wrap with
coalesce(field, '')
Checking
result["error"]
exists
Always present; true error is
!= null
Use
result.get("error") is not None
Flow deployed but state is "Stopped"
Flow won't run on schedule
Check connection auth; re-enable
Teams "Chat with Flow bot" recipient as object
400
GraphUserDetailNotFound
Use plain string with trailing semicolon (see below)
Teams
PostMessageToConversation
— Recipient Formats
The
body/recipient
parameter format depends on the
location
value:
Location
body/recipient
format
Example
Chat with Flow bot
Plain email string with
trailing semicolon
"user@contoso.com;"
Channel
Object with
groupId
and
channelId
{"groupId": "...", "channelId": "..."}
Common mistake
passing {"to": "user@contoso.com"} for "Chat with Flow bot" returns a 400 GraphUserDetailNotFound error. The API expects a plain string. Reference Files flow-schema.md — Full flow definition JSON schema trigger-types.md — Trigger type templates action-patterns-core.md — Variables, control flow, expressions action-patterns-data.md — Array transforms, HTTP, parsing action-patterns-connectors.md — SharePoint, Outlook, Teams, Approvals build-patterns.md — Complete flow definition templates (Recurrence+SP+Teams, HTTP trigger)
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