/flowstudio-power-automate-build

name: flowstudio-power-automate-build
description: >-
  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

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 = "<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_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