flowstudio-power-automate-build

github/awesome-copilot · updated Apr 8, 2026

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$npx skills add https://github.com/github/awesome-copilot --skill flowstudio-power-automate-build
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summary

Programmatically build, scaffold, and deploy Power Automate cloud flows via FlowStudio MCP.

  • Requires a FlowStudio MCP subscription and valid JWT token; connection setup covered in the flowstudio-power-automate-mcp skill
  • Covers the full build workflow: safety checks for existing flows, connection reference discovery, definition construction, deployment (create or update), and test execution
  • Includes reference templates for triggers, core actions (variables, control flow, expressions),
skill.md

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 = "<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

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}"
how to use flowstudio-power-automate-build

How to use flowstudio-power-automate-build on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add flowstudio-power-automate-build
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/github/awesome-copilot --skill flowstudio-power-automate-build

The skills CLI fetches flowstudio-power-automate-build from GitHub repository github/awesome-copilot and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/flowstudio-power-automate-build

Reload or restart Cursor to activate flowstudio-power-automate-build. Access the skill through slash commands (e.g., /flowstudio-power-automate-build) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.863 reviews
  • William Wang· Dec 28, 2024

    flowstudio-power-automate-build reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Naina Sharma· Dec 24, 2024

    flowstudio-power-automate-build fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Mia Iyer· Dec 24, 2024

    flowstudio-power-automate-build has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Omar Jain· Dec 20, 2024

    Keeps context tight: flowstudio-power-automate-build is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Pratham Ware· Dec 16, 2024

    We added flowstudio-power-automate-build from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Ava Nasser· Dec 8, 2024

    flowstudio-power-automate-build is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Isabella Jackson· Dec 4, 2024

    Useful defaults in flowstudio-power-automate-build — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Noor Brown· Nov 27, 2024

    flowstudio-power-automate-build reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Zara Brown· Nov 23, 2024

    I recommend flowstudio-power-automate-build for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Omar Harris· Nov 19, 2024

    flowstudio-power-automate-build is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

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