flowstudio-power-automate-mcp

github/awesome-copilot · updated Apr 8, 2026

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

Programmatic Power Automate flow management via FlowStudio MCP server.

  • List, read, and monitor cloud flows directly from the Power Automate API without UI or manual steps
  • Inspect run history, per-action error details, and trigger outputs; resubmit failed runs or cancel active executions
  • Update flow definitions, manage connections, and retrieve HTTP-triggered flow callback URLs
  • Requires FlowStudio MCP subscription with JWT token authentication; Python or Node.js helper functions pr
skill.md

Power Automate via FlowStudio MCP

This skill lets AI agents read, monitor, and operate Microsoft Power Automate cloud flows programmatically through a FlowStudio MCP server — no browser, no UI, no manual steps.

Requires: A FlowStudio MCP subscription (or compatible Power Automate MCP server). You will need:

  • MCP endpoint: https://mcp.flowstudio.app/mcp (same for all subscribers)
  • API key / JWT token (x-api-key header — NOT Bearer)
  • Power Platform environment name (e.g. Default-<tenant-guid>)

Source of Truth

Priority Source Covers
1 Real API response Always trust what the server actually returns
2 tools/list Tool names, parameter names, types, required flags
3 SKILL docs & reference files Response shapes, behavioral notes, workflow recipes

Start every new session with tools/list. It returns the authoritative, up-to-date schema for every tool — parameter names, types, and required flags. The SKILL docs cover what tools/list cannot tell you: response shapes, non-obvious behaviors, and end-to-end workflow patterns.

If any documentation disagrees with tools/list or a real API response, the API wins.


Recommended Language: Python or Node.js

All examples in this skill and the companion build / debug skills use Python with urllib.request (stdlib — no pip install needed). Node.js is an equally valid choice: fetch is built-in from Node 18+, JSON handling is native, and the async/await model maps cleanly onto the request-response pattern of MCP tool calls — making it a natural fit for teams already working in a JavaScript/TypeScript stack.

Language Verdict Notes
Python ✅ Recommended Clean JSON handling, no escaping issues, all skill examples use it
Node.js (≥ 18) ✅ Recommended Native fetch + JSON.stringify/JSON.parse; async/await fits MCP call patterns well; no extra packages needed
PowerShell ⚠️ Avoid for flow operations ConvertTo-Json -Depth silently truncates nested definitions; quoting and escaping break complex payloads. Acceptable for a quick tools/list discovery call but not for building or updating flows.
cURL / Bash ⚠️ Possible but fragile Shell-escaping nested JSON is error-prone; no native JSON parser

TL;DR — use the Core MCP Helper (Python or Node.js) below. Both handle JSON-RPC framing, auth, and response parsing in a single reusable function.


What You Can Do

FlowStudio MCP has two access tiers. FlowStudio for Teams subscribers get both the fast Azure-table store (cached snapshot data + governance metadata) and full live Power Automate API access. MCP-only subscribers get the live tools — more than enough to build, debug, and operate flows.

Live Tools — Available to All MCP Subscribers

Tool What it does
list_live_flows List flows in an environment directly from the PA API (always current)
list_live_environments List all Power Platform environments visible to the service account
list_live_connections List all connections in an environment from the PA API
get_live_flow Fetch the complete flow definition (triggers, actions, parameters)
get_live_flow_http_schema Inspect the JSON body schema and response schemas of an HTTP-triggered flow
get_live_flow_trigger_url Get the current signed callback URL for an HTTP-triggered flow
trigger_live_flow POST to an HTTP-triggered flow's callback URL (AAD auth handled automatically)
update_live_flow Create a new flow or patch an existing definition in one call
add_live_flow_to_solution Migrate a non-solution flow into a solution
get_live_flow_runs List recent run history with status, start/end times, and errors
get_live_flow_run_error Get structured error details (per-action) for a failed run
get_live_flow_run_action_outputs Inspect inputs/outputs of any action (or every foreach iteration) in a run
resubmit_live_flow_run Re-run a failed or cancelled run using its original trigger payload
cancel_live_flow_run Cancel a currently running flow execution

Store Tools — FlowStudio for Teams Subscribers Only

These tools read from (and write to) the FlowStudio Azure table — a monitored snapshot of your tenant's flows enriched with governance metadata and run statistics.

Tool What it does
list_store_flows Search flows from the cache with governance flags, run failure rates, and owner metadata
get_store_flow Get full cached details for a single flow including run stats and governance fields
get_store_flow_trigger_url Get the trigger URL from the cache (instant, no PA API call)
get_store_flow_runs Cached run history for the last N days with duration and remediation hints
get_store_flow_errors Cached failed-only runs with failed action names and remediation hints
get_store_flow_summary Aggregated stats: success rate, failure count, avg/max duration
set_store_flow_state Start or stop a flow via the PA API and sync the result back to the store
update_store_flow Update governance metadata (description, tags, monitor flag, notification rules, business impact)
list_store_environments List all environments from the cache
list_store_makers List all makers (citizen developers) from the cache
get_store_maker Get a maker's flow/app counts and account status
list_store_power_apps List all Power Apps canvas apps from the cache
list_store_connections List all Power Platform connections from the cache

Which Tool Tier to Call First

Task Tool Notes
List flows list_live_flows Always current — calls PA API directly
Read a definition get_live_flow Always fetched live — not cached
Debug a failure get_live_flow_runsget_live_flow_run_error Use live run data

⚠️ list_live_flows returns a wrapper object with a flows array — access via result["flows"].

Store tools (list_store_flows, get_store_flow, etc.) are available to FlowStudio for Teams subscribers and provide cached governance metadata. Use live tools when in doubt — they work for all subscription tiers.


Step 0 — Discover Available Tools

Always start by calling tools/list to confirm the server is reachable and see exactly which tool names are available (names may vary by server version):

import json, urllib.request

TOKEN = "<YOUR_JWT_TOKEN>"
MCP   = "https://mcp.flowstudio.app/mcp"

def mcp_raw(method, params=None, cid=1):
    payload = {"jsonrpc": "2.0", "method": method, "id": cid}
    if params:
        payload["params"] = params
    req = urllib.request.Request(MCP, data=json.dumps(payload).encode(),
        headers={"x-api-key": TOKEN, "Content-Type": "application/json",
                 "User-Agent": "FlowStudio-MCP/1.0"})
    try:
        resp = urllib.request.urlopen(req, timeout=30)
    except urllib.error.HTTPError as e:
        raise RuntimeError(f"MCP HTTP {e.code} — check token and endpoint") from e
    return json.loads(resp.read())

raw = mcp_raw("tools/list")
if "error" in raw:
    print("ERROR:", raw["error"]); raise SystemExit(1)
for t in raw["result"]["tools"]:
    print(t["name"], "—", t["description"][:60])

Core MCP Helper (Python)

Use this helper throughout all subsequent operations:

import json, urllib.request

TOKEN = "<YOUR_JWT_TOKEN>"
MCP   = "https://mcp.flowstudio.app/mcp"

def mcp(tool, args, cid=1):
    payload = {"jsonrpc": "2.0", "method": "tools/call", "id": cid,
               "params": {"name": tool, "arguments": args}}
    req = urllib.request.Request(MCP, data=json.dumps(payload).encode(),
        headers={"x-api-key": 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'])}")
    text = raw["result"]["content"][0]["text"]
    return json.loads(text)

Common auth errors:

  • HTTP 401/403 → token is missing, expired, or malformed. Get a fresh JWT from mcp.flowstudio.app.
  • HTTP 400 → malformed JSON-RPC payload. Check Content-Type: application/json and body structure.
  • MCP error: {"code": -32602, ...} → wrong or missing tool arguments.

Core MCP Helper (Node.js)

Equivalent helper for Node.js 18+ (built-in fetch — no packages required):

how to use flowstudio-power-automate-mcp

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

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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-mcp
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-mcp

The skills CLI fetches flowstudio-power-automate-mcp 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-mcp

Reload or restart Cursor to activate flowstudio-power-automate-mcp. Access the skill through slash commands (e.g., /flowstudio-power-automate-mcp) 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.

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Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.661 reviews
  • Charlotte Mensah· Dec 24, 2024

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

  • Sofia Lopez· Dec 16, 2024

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

  • Pratham Ware· Dec 8, 2024

    Registry listing for flowstudio-power-automate-mcp matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Min Ghosh· Dec 8, 2024

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

  • Charlotte Okafor· Dec 8, 2024

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

  • Sakshi Patil· Nov 27, 2024

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

  • Kabir Martinez· Nov 27, 2024

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

  • Advait Martin· Nov 27, 2024

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

  • Alexander Tandon· Nov 27, 2024

    Solid pick for teams standardizing on skills: flowstudio-power-automate-mcp is focused, and the summary matches what you get after install.

  • Kabir Jain· Nov 15, 2024

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

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