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

Workflow:

1. Load current build tools.
2. Check for an existing flow.
3. Resolve connection references.
4. Build the definition.
5. Deploy.
6. Verify.
7. Test.

---

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 build 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 = ""

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

---

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_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 — 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](references/flow-schema.md) for the full schema and these action pattern references for copy-paste templates:

• [action-patterns-core.md](references/action-patterns-core.md) — Variables, control flow, expressions
• [action-patterns-data.md](references/action-patterns-data.md) — Array transforms, HTTP, parsing
• [action-patterns-connectors.md](references/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](references/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": "", "table": ""},
    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_flow always returns an error key. > null (Python None) means success — do not treat the presence of the key as failure. > > ⚠️ Flow description lives at definition["description"]. The current server > appends #flowstudio-mcp for usage tracking. Do not pass a top-level > description argument unless tool_search shows 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_flow > or resubmit_live_flow_run.

Updated flows (have prior runs) — ANY trigger type

> Use resubmit_live_flow_run first. 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-triggered 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']}")

Brand-new non-HTTP flows (Recurrence, connector triggers, etc.)

A brand-new Recurrence or connector-triggered flow has no prior runs to resubmit and no HTTP endpoint to call. This is the ONLY scenario where you need the temporary HTTP trigger approach below. Deploy with a temporary HTTP trigger first, test the actions, then swap to the production trigger.

Compact recipe:

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["created"]

test = 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 trigger_live_flow.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 | Alway

…

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: ninihen1
• Source: ninihen1/power-automate-mcp-skills
• License: MIT

Install and usage instructions live in the source repository linked above.