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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.

Install / Use

npx skills add github/awesome-copilot --skill flowstudio-power-automate-build

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

90/100

Category

Automation

Supported Platforms

Universal

Our assessment of flowstudio-power-automate-build

flowstudio-power-automate-build scores 90/100 on our quality scale, 283rd of 1,111 Automation skills we index (top 26%).

Its SKILL.md is 19 KB long, well organised into 34 sections with 18 code examples: a thorough specification that gives an agent plenty to work with.

With 39,348 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
30/30
Structure
20/20
Description
15/15
Adoption
20/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated yesterday, so flowstudio-power-automate-build is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

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All 4 of these similar skills score higher than flowstudio-power-automate-build; compare them before choosing.

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Frequently asked questions

How do I install flowstudio-power-automate-build?
Run npx skills add github/awesome-copilot --skill flowstudio-power-automate-build. The install tabs above show the steps for each supported agent.
Which AI agents does flowstudio-power-automate-build work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is flowstudio-power-automate-build safe to use?
It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is flowstudio-power-automate-build still maintained?
The repository was last updated yesterday, so flowstudio-power-automate-build is actively maintained.

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 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:

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_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 `c

Truncated for display — read the full file on GitHub.

Related Skills

View on GitHub
GitHub Stars39.3k
CategoryAutomation
Updated1d ago
Forks5.0k

Languages

JavaScript

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions