
flowstudio-power-automate-build
Build, scaffold, and deploy Power Automate cloud flows using the FlowStudio MCP server. Your agent constructs flow definitions, wires connections, deploys, and tests — all via MCP without opening the portal. Load this skill when asked to: create a flow, build a new flow, deploy a flow definition, scaffold a Power Automate workflow, construct a flow JSON, update an existing flow's actions, patch a flow definition, add actions to a flow, wire up connections, or generate a workflow definition from scratch. Requires a FlowStudio MCP subscription — see https://mcp.flowstudio.app
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/github/awesome-copilot --skill flowstudio-power-automate-build- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads flowstudio-power-automate-build automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
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
Workflow:
- Load current build tools.
- Check for an existing flow.
- Resolve connection references.
- Build the definition.
- Deploy.
- Verify.
- Test.
Source of Truth
Always call
list_skills/tool_searchfirst 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 build patterns — things tool schemas cannot tell you. If this document disagrees withtool_searchor 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
0. Load the Current Build Tools
For a brand-new flow, load the server's create-flow bundle. For editing an
existing flow, load build-flow. This keeps the agent aligned with the MCP
server's current schema before constructing JSON.
schemas = mcp("tool_search", query="skill:create-flow")
# Includes list_live_environments, list_live_connections,
# describe_live_connector, get_live_dynamic_options, update_live_flow.
If you need a tool outside the bundle, load it explicitly:
mcp("tool_search", query="select:get_live_dynamic_properties")
1. Safety Check: Does the Flow Already Exist?
Always look before you build to avoid duplicates:
results = mcp("list_live_flows",
environmentName=ENV,
mode="owner",
search="My New Flow",
top=20)
# list_live_flows returns { "flows": [...], "mode": "...", ... }
matches = [f for f in results["flows"]
if "My New Flow".lower() in f["displayName"].lower()]
if len(matches) > 0:
# Flow exists — modify rather than create
FLOW_ID = matches[0]["id"] # plain UUID from list_live_flows
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
For very large environments, list_live_flows may return a continuation URL.
Pass it back as continuationUrl with the same mode to retrieve the next
batch. Use mode="admin" only when the user needs all environment flows and
the MCP identity has admin rights.
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_connectionsfirst — 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 — Find active connections
conns = mcp("list_live_connections", environmentName=ENV)
active = [c for c in conns["connections"]
if c["statuses"][0]["status"] == "Connected"]
conn_map = {c["connectorName"]: c["id"] for c in active}
For a known connector, pass search to reduce output and get paste-ready
connectionReferenceTemplate and hostTemplate values:
sp_conns = mcp("list_live_connections",
environmentName=ENV,
search="shared_sharepointonline")
2b — Determine which connectors the flow needs
Common connector API names: SharePoint shared_sharepointonline, Outlook
shared_office365, Teams shared_teams, Approvals shared_approvals,
OneDrive shared_onedriveforbusiness, Excel shared_excelonlinebusiness,
Dataverse shared_commondataserviceforapps, Forms shared_microsoftforms.
Flows that need no connectors, such as Recurrence + Compose + HTTP only, can
omit connectionReferences.
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 missing:
# STOP: connections require browser OAuth consent.
# Ask the user to create the missing connector connections in the
# selected environment, then re-run list_live_connections.
raise Exception(f"Missing active connections: {missing}")
2d — Build the connectionReferences block
connection_references = {}
host_templates = {}
for connector in connectors_needed:
c = next(c for c in active if c["connectorName"] == connector)
connection_references[connector] = c.get("connectionReferenceTemplate") or {
"connectionName": c["id"], # the connection id from list_live_connections
"source": "Invoker",
"id": f"/providers/Microsoft.PowerApps/apis/{connector}"
}
host_templates[connector] = c.get("hostTemplate") or {
"connectionName": connector
}
In Step 3 action JSON, inputs.host.connectionName must be the map key such as
shared_teams, not the GUID. The GUID belongs only inside the
connectionReferences[connector].connectionName value. If an existing flow uses
the same connectors, you may also copy its properties.connectionReferences
from get_live_flow.
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.
Discover connector operations before guessing JSON
For connector-backed triggers/actions, prefer the live connector describer over hand-written shapes. It can return authored hints, canonical examples, variant keys, inputs/outputs, and dynamic metadata pointers.
# Search across connectors when you know the user's intent but not the API.
matches = mcp("describe_live_connector",
environmentName=ENV,
search="send email",
top=5)
# Describe a specific operation before copying an exampleDefinition.
op = mcp("describe_live_connector",
environmentName=ENV,
connectorName="shared_office365",
operationId="SendEmailV2")
print(op.get("hint"))
When an operation has multiple authored variants, request the variant the flow needs:
teams_chat = mcp("describe_live_connector",
environmentName=ENV,
connectorName="shared_teams",
operationId="PostMessageToConversation",
variant="flowbot_chat")
When the operation description says a parameter has dynamic options or dynamic properties, call the indicated next tool:
sp_op = mcp("describe_live_connector",
environmentName=ENV,
connectorName="shared_sharepointonline",
operationId="GetItems")
sites = mcp("get_live_dynamic_options",
environmentName=ENV,
connectorName="shared_sharepointonline",
connectionName=conn_map["shared_sharepointonline"],
operationId="GetItems",
parameterName="dataset",
dynamicMetadata=sp_op["dynamicParameters"]["dataset"])
fields = mcp("get_live_dynamic_properties",
environmentName=ENV,
connectorName="shared_sharepointonline",
connectionName=conn_map["shared_sharepointonline"],
operationId="GetItems",
parameterName="item",
parameters={"dataset": "<site-url>", "table": "<list-id>"},
dynamicMetadata=sp_op["dynamicProperties"]["item"])
Use dynamic options for dropdown IDs such as SharePoint sites/lists and Teams teams/channels. Use dynamic properties for schema/field shapes such as SharePoint list item columns.
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:
definition["description"] = "Weekly SharePoint → Teams notification flow, built by agent"
result = mcp("update_live_flow",
environmentName=ENV,
# flowName omitted → creates a new flow
definition=definition,
connectionReferences=connection_references,
displayName="Overdue Invoice Notifications"
)
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:
definition["description"] = (
"Updated by agent on " + __import__('datetime').datetime.utcnow().isoformat()
)
result = mcp("update_live_flow",
environmentName=ENV,
flowName=FLOW_ID,
definition=definition,
connectionReferences=connection_references,
displayName="My Updated Flow"
)
if result.get("error") is not None:
print("Update failed:", result["error"])
else:
print("Update succeeded:", result)
⚠️
update_live_flowalways returns anerrorkey.null(PythonNone) means success — do not treat the presence of the key as failure.⚠️ Flow description lives at
definition["description"]. The current server appends#flowstudio-mcpfor usage tracking. Do not pass a top-leveldescriptionargument unlesstool_searchshows one in the active schema.
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 |
5. Verify the Deployment
check = mcp("get_live_flow", environmentName=ENV, flowName=FLOW_ID)
# Confirm state
print("State:", check["properties"]["state"]) # Should be "Started"
# If state is "Stopped", use set_live_flow_state — NOT update_live_flow
# mcp("set_live_flow_state", environmentName=ENV, flowName=FLOW_ID, state="Started")
# Confirm the action we added is there
acts = check["properties"]["definition"]["actions"]
print("Actions:", list(acts.keys()))
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_floworresubmit_live_flow_run.
Updated flows (have prior runs) — ANY trigger type
Use
resubmit_live_flow_runfirst. It works for EVERY trigger type — Recurrence, SharePoint, connector webhooks, Button, and HTTP. It replays the original trigger payload. Do NOT ask the user to manually trigger the flow or wait for the next scheduled run.
runs = mcp("get_live_flow_runs", environmentName=ENV, flowName=FLOW_ID, top=1)
if runs:
# Works for Recurrence, SharePoint, connector triggers — not just HTTP
result = mcp("resubmit_live_flow_run",
environmentName=ENV, flowName=FLOW_ID, runName=runs[0]["name"])
print(result) # {"resubmitted": true, "triggerName": "..."}
HTTP, Button, and PowerApps flows — custom test payload
Only use trigger_live_flow when you need to send a different payload
than the original run. For verifying a fix, resubmit_live_flow_run is
better because it uses the exact data that caused the failure.
defn = mcp("get_live_flow", environmentName=ENV, flowName=FLOW_ID)
triggers = defn["properties"]["definition"]["triggers"]
manual = next(iter(triggers.values()))
print("Expected body:", manual.get("inputs", {}).get("schema"))
result = mcp("trigger_live_flow",
environmentName=ENV, flowName=FLOW_ID,
body={"name": "Test", "value": 1})
print(f"Status: {result['responseStatus']}, via: {result['invocation']}")
print(result.get("warning")) # set when a required input was missing: the run still ran, with null
Brand-new non-HTTP flows
A brand-new Recurrence flow needs no workaround: deploy it, then run it
immediately with trigger_live_flow and no body — same as the portal's
"Run flow" button. A body is refused; scheduled triggers take no inputs.
A brand-new connector-triggered flow (SharePoint, webhooks) has no prior runs and cannot fire without a real source event. Deploy with a temporary HTTP trigger, test the actions, then swap to the production trigger:
production_trigger = definition["triggers"]
definition["triggers"] = {
"manual": {"type": "Request", "kind": "Http", "inputs": {"schema": {}}}
}
result = mcp("update_live_flow", environmentName=ENV,
flowName=FLOW_ID, # omit if creating new
definition=definition, connectionReferences=connection_references,
displayName="Overdue Invoice Notifications")
FLOW_ID = FLOW_ID or result["flowName"]
mcp("trigger_live_flow", environmentName=ENV, flowName=FLOW_ID,
body={"sample": "payload"})
runs = mcp("get_live_flow_runs", environmentName=ENV, flowName=FLOW_ID, top=1)
if runs[0]["status"] == "Failed":
err = mcp("get_live_flow_run_error",
environmentName=ENV, flowName=FLOW_ID, runName=runs[0]["name"])
raise Exception(err["failedActions"][-1])
definition["triggers"] = production_trigger
mcp("update_live_flow", environmentName=ENV, flowName=FLOW_ID,
definition=definition, connectionReferences=connection_references)
The trigger is only the entry point; testing through HTTP still exercises the
same actions. If actions use triggerBody() or triggerOutputs(), pass a
representative body shaped like the production trigger payload.
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 | Call set_live_flow_state with state: "Started" — do not use update_live_flow for state changes |
| Teams "Chat with Flow bot" recipient as object | 400 GraphUserDetailNotFound | Use plain string with trailing semicolon (see below) |
| Copilot/Skills flow not in a solution | Copilot Studio may not discover it as an agent tool | After deploy, call add_live_flow_to_solution with the target solutionId |
| Button/Skills trigger used for MCP testing | Runs even when a required input is missing (null) | Pass inputs in trigger_live_flow body; on warning, cancel and retry with the full body |
Connector action missing metadata.operationMetadataId | Designer/run-only UI can behave inconsistently | Preserve existing IDs; add stable GUIDs for new connector actions |
Placeholder Excel scriptId | Dynamic validation fails at save time | Resolve the real Office Script ID before deploying |
SharePoint PatchItem omits required fields | Save can fail even if the field is not changing | Echo unchanged required fields such as item/Title |
| Copilot Studio connector calls a draft agent | Connector invocation can fail or hit stale behavior | Publish the agent before testing/resubmitting the flow |
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 400GraphUserDetailNotFounderror. 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)
Related Skills
flowstudio-power-automate-mcp— Core connection setup and tool referenceflowstudio-power-automate-debug— Debug failing flows after deployment
FAQ
What does the flowstudio-power-automate-build skill do?
Build, scaffold, and deploy Power Automate cloud flows using the FlowStudio MCP server. Your agent constructs flow definitions, wires connections, deploys, and tests — all via MCP without opening the portal. Load this skill when asked to: create a flow, build a new flow, deploy a flow definition, scaffold a Power Automate workflow, construct a flow JSON, update an existing flow's actions, patch a flow definition, add actions to a flow, wire up connections, or generate a workflow definition from scratch. Requires a FlowStudio MCP subscription — see https://mcp.flowstudio.app
How do I install flowstudio-power-automate-build?
Run npx skills add https://github.com/github/awesome-copilot --skill flowstudio-power-automate-build in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/flowstudio-power-automate-build/ (personal) or .claude/skills/flowstudio-power-automate-build/ (project).
Which AI agents can use flowstudio-power-automate-build?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is flowstudio-power-automate-build safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains flowstudio-power-automate-build?
It is published by github in github/awesome-copilot, and it is an official skill from the maker of the technology it covers. It has 1,938 recorded installs.
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