flowstudio-power-automate-mcp

Connect to and operate Power Automate cloud flows via a FlowStudio MCP server. Use when asked to: list flows, read a flow definition, check run history, inspect action outputs, resubmit a run, cancel a running flow, view connections, get a trigger URL, validate a definition, monitor flow health, or any task that requires talking to the Power Automate API through an MCP tool. Also use for Power Platform environment discovery and connection management. Requires a FlowStudio MCP subscription or compatible server — see https://mcp.flowstudio.app

25 stars

Best use case

flowstudio-power-automate-mcp is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Connect to and operate Power Automate cloud flows via a FlowStudio MCP server. Use when asked to: list flows, read a flow definition, check run history, inspect action outputs, resubmit a run, cancel a running flow, view connections, get a trigger URL, validate a definition, monitor flow health, or any task that requires talking to the Power Automate API through an MCP tool. Also use for Power Platform environment discovery and connection management. Requires a FlowStudio MCP subscription or compatible server — see https://mcp.flowstudio.app

Teams using flowstudio-power-automate-mcp should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/flowstudio-power-automate-mcp/SKILL.md --create-dirs "https://raw.githubusercontent.com/ComeOnOliver/skillshub/main/skills/github/awesome-copilot/flowstudio-power-automate-mcp/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/flowstudio-power-automate-mcp/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How flowstudio-power-automate-mcp Compares

Feature / Agentflowstudio-power-automate-mcpStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Connect to and operate Power Automate cloud flows via a FlowStudio MCP server. Use when asked to: list flows, read a flow definition, check run history, inspect action outputs, resubmit a run, cancel a running flow, view connections, get a trigger URL, validate a definition, monitor flow health, or any task that requires talking to the Power Automate API through an MCP tool. Also use for Power Platform environment discovery and connection management. Requires a FlowStudio MCP subscription or compatible server — see https://mcp.flowstudio.app

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# 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](https://mcp.flowstudio.app) 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_runs` → `get_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):

```python
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:

```python
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](https://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):

```js
const TOKEN = "<YOUR_JWT_TOKEN>";
const MCP   = "https://mcp.flowstudio.app/mcp";

async function mcp(tool, args, cid = 1) {
  const payload = {
    jsonrpc: "2.0",
    method: "tools/call",
    id: cid,
    params: { name: tool, arguments: args },
  };
  const res = await fetch(MCP, {
    method: "POST",
    headers: {
      "x-api-key": TOKEN,
      "Content-Type": "application/json",
      "User-Agent": "FlowStudio-MCP/1.0",
    },
    body: JSON.stringify(payload),
  });
  if (!res.ok) {
    const body = await res.text();
    throw new Error(`MCP HTTP ${res.status}: ${body.slice(0, 200)}`);
  }
  const raw = await res.json();
  if (raw.error) throw new Error(`MCP error: ${JSON.stringify(raw.error)}`);
  return JSON.parse(raw.result.content[0].text);
}
```

> Requires Node.js 18+. For older Node, replace `fetch` with `https.request`
> from the stdlib or install `node-fetch`.

---

## List Flows

```python
ENV = "Default-<tenant-guid>"

result = mcp("list_live_flows", {"environmentName": ENV})
# Returns wrapper object:
# {"mode": "owner", "flows": [{"id": "0757041a-...", "displayName": "My Flow",
#   "state": "Started", "triggerType": "Request", ...}], "totalCount": 42, "error": null}
for f in result["flows"]:
    FLOW_ID = f["id"]   # plain UUID — use directly as flowName
    print(FLOW_ID, "|", f["displayName"], "|", f["state"])
```

---

## Read a Flow Definition

```python
FLOW = "<flow-uuid>"

flow = mcp("get_live_flow", {"environmentName": ENV, "flowName": FLOW})

# Display name and state
print(flow["properties"]["displayName"])
print(flow["properties"]["state"])

# List all action names
actions = flow["properties"]["definition"]["actions"]
print("Actions:", list(actions.keys()))

# Inspect one action's expression
print(actions["Compose_Filter"]["inputs"])
```

---

## Check Run History

```python
# Most recent runs (newest first)
runs = mcp("get_live_flow_runs", {"environmentName": ENV, "flowName": FLOW, "top": 5})
# Returns direct array:
# [{"name": "08584296068667933411438594643CU15",
#   "status": "Failed",
#   "startTime": "2026-02-25T06:13:38.6910688Z",
#   "endTime": "2026-02-25T06:15:24.1995008Z",
#   "triggerName": "manual",
#   "error": {"code": "ActionFailed", "message": "An action failed..."}},
#  {"name": "08584296028664130474944675379CU26",
#   "status": "Succeeded", "error": null, ...}]

for r in runs:
    print(r["name"], r["status"])

# Get the name of the first failed run
run_id = next((r["name"] for r in runs if r["status"] == "Failed"), None)
```

---

## Inspect an Action's Output

```python
run_id = runs[0]["name"]

out = mcp("get_live_flow_run_action_outputs", {
    "environmentName": ENV,
    "flowName": FLOW,
    "runName": run_id,
    "actionName": "Get_Customer_Record"   # exact action name from the definition
})
print(json.dumps(out, indent=2))
```

---

## Get a Run's Error

```python
err = mcp("get_live_flow_run_error", {
    "environmentName": ENV,
    "flowName": FLOW,
    "runName": run_id
})
# Returns:
# {"runName": "08584296068...",
#  "failedActions": [
#    {"actionName": "HTTP_find_AD_User_by_Name", "status": "Failed",
#     "code": "NotSpecified", "startTime": "...", "endTime": "..."},
#    {"actionName": "Scope_prepare_workers", "status": "Failed",
#     "error": {"code": "ActionFailed", "message": "An action failed..."}}
#  ],
#  "allActions": [
#    {"actionName": "Apply_to_each", "status": "Skipped"},
#    {"actionName": "Compose_WeekEnd", "status": "Succeeded"},
#    ...
#  ]}

# The ROOT cause is usually the deepest entry in failedActions:
root = err["failedActions"][-1]
print(f"Root failure: {root['actionName']} → {root['code']}")
```

---

## Resubmit a Run

```python
result = mcp("resubmit_live_flow_run", {
    "environmentName": ENV,
    "flowName": FLOW,
    "runName": run_id
})
print(result)   # {"resubmitted": true, "triggerName": "..."}
```

---

## Cancel a Running Run

```python
mcp("cancel_live_flow_run", {
    "environmentName": ENV,
    "flowName": FLOW,
    "runName": run_id
})
```

> ⚠️ **Do NOT cancel a run that shows `Running` because it is waiting for an
> adaptive card response.** That status is normal — the flow is paused waiting
> for a human to respond in Teams. Cancelling it will discard the pending card.

---

## Full Round-Trip Example — Debug and Fix a Failing Flow

```python
# ── 1. Find the flow ─────────────────────────────────────────────────────
result = mcp("list_live_flows", {"environmentName": ENV})
target = next(f for f in result["flows"] if "My Flow Name" in f["displayName"])
FLOW_ID = target["id"]

# ── 2. Get the most recent failed run ────────────────────────────────────
runs = mcp("get_live_flow_runs", {"environmentName": ENV, "flowName": FLOW_ID, "top": 5})
# [{"name": "08584296068...", "status": "Failed", ...}, ...]
RUN_ID = next(r["name"] for r in runs if r["status"] == "Failed")

# ── 3. Get per-action failure breakdown ──────────────────────────────────
err = mcp("get_live_flow_run_error", {"environmentName": ENV, "flowName": FLOW_ID, "runName": RUN_ID})
# {"failedActions": [{"actionName": "HTTP_find_AD_User_by_Name", "code": "NotSpecified",...}], ...}
root_action = err["failedActions"][-1]["actionName"]
print(f"Root failure: {root_action}")

# ── 4. Read the definition and inspect the failing action's expression ───
defn = mcp("get_live_flow", {"environmentName": ENV, "flowName": FLOW_ID})
acts = defn["properties"]["definition"]["actions"]
print("Failing action inputs:", acts[root_action]["inputs"])

# ── 5. Inspect the prior action's output to find the null ────────────────
out = mcp("get_live_flow_run_action_outputs", {
    "environmentName": ENV, "flowName": FLOW_ID,
    "runName": RUN_ID, "actionName": "Compose_Names"
})
nulls = [x for x in out.get("body", []) if x.get("Name") is None]
print(f"{len(nulls)} records with null Name")

# ── 6. Apply the fix ─────────────────────────────────────────────────────
acts[root_action]["inputs"]["parameters"]["searchName"] = \
    "@coalesce(item()?['Name'], '')"

conn_refs = defn["properties"]["connectionReferences"]
result = mcp("update_live_flow", {
    "environmentName": ENV, "flowName": FLOW_ID,
    "definition": defn["properties"]["definition"],
    "connectionReferences": conn_refs
})
assert result.get("error") is None, f"Deploy failed: {result['error']}"
# ⚠️ error key is always present — only fail if it is NOT None

# ── 7. Resubmit and verify ───────────────────────────────────────────────
mcp("resubmit_live_flow_run", {"environmentName": ENV, "flowName": FLOW_ID, "runName": RUN_ID})

import time; time.sleep(30)
new_runs = mcp("get_live_flow_runs", {"environmentName": ENV, "flowName": FLOW_ID, "top": 1})
print(new_runs[0]["status"])   # Succeeded = done
```

---

## Auth & Connection Notes

| Field | Value |
|---|---|
| Auth header | `x-api-key: <JWT>` — **not** `Authorization: Bearer` |
| Token format | Plain JWT — do not strip, alter, or prefix it |
| Timeout | Use ≥ 120 s for `get_live_flow_run_action_outputs` (large outputs) |
| Environment name | `Default-<tenant-guid>` (find it via `list_live_environments` or `list_live_flows` response) |

---

## Reference Files

- [MCP-BOOTSTRAP.md](references/MCP-BOOTSTRAP.md) — endpoint, auth, request/response format (read this first)
- [tool-reference.md](references/tool-reference.md) — response shapes and behavioral notes (parameters are in `tools/list`)
- [action-types.md](references/action-types.md) — Power Automate action type patterns
- [connection-references.md](references/connection-references.md) — connector reference guide

---

## More Capabilities

For **diagnosing failing flows** end-to-end → load the `power-automate-debug` skill.

For **building and deploying new flows** → load the `power-automate-build` skill.

Related Skills

preprocessing-data-with-automated-pipelines

25
from ComeOnOliver/skillshub

Process automate data cleaning, transformation, and validation for ML tasks. Use when requesting "preprocess data", "clean data", "ETL pipeline", or "data transformation". Trigger with relevant phrases based on skill purpose.

powerbi-modeling

25
from ComeOnOliver/skillshub

Power BI semantic modeling assistant for building optimized data models. Use when working with Power BI semantic models, creating measures, designing star schemas, configuring relationships, implementing RLS, or optimizing model performance. Triggers on queries about DAX calculations, table relationships, dimension/fact table design, naming conventions, model documentation, cardinality, cross-filter direction, calculation groups, and data model best practices. Always connects to the active model first using power-bi-modeling MCP tools to understand the data structure before providing guidance.

power-platform-mcp-connector-suite

25
from ComeOnOliver/skillshub

Generate complete Power Platform custom connector with MCP integration for Copilot Studio - includes schema generation, troubleshooting, and validation

power-bi-report-design-consultation

25
from ComeOnOliver/skillshub

Power BI report visualization design prompt for creating effective, user-friendly, and accessible reports with optimal chart selection and layout design.

power-bi-performance-troubleshooting

25
from ComeOnOliver/skillshub

Systematic Power BI performance troubleshooting prompt for identifying, diagnosing, and resolving performance issues in Power BI models, reports, and queries.

power-bi-model-design-review

25
from ComeOnOliver/skillshub

Comprehensive Power BI data model design review prompt for evaluating model architecture, relationships, and optimization opportunities.

power-bi-dax-optimization

25
from ComeOnOliver/skillshub

Comprehensive Power BI DAX formula optimization prompt for improving performance, readability, and maintainability of DAX calculations.

power-apps-code-app-scaffold

25
from ComeOnOliver/skillshub

Scaffold a complete Power Apps Code App project with PAC CLI setup, SDK integration, and connector configuration

flowstudio-power-automate-debug

25
from ComeOnOliver/skillshub

Debug failing Power Automate cloud flows using the FlowStudio MCP server. Load this skill when asked to: debug a flow, investigate a failed run, why is this flow failing, inspect action outputs, find the root cause of a flow error, fix a broken Power Automate flow, diagnose a timeout, trace a DynamicOperationRequestFailure, check connector auth errors, read error details from a run, or troubleshoot expression failures. Requires a FlowStudio MCP subscription — see https://mcp.flowstudio.app

flowstudio-power-automate-build

25
from ComeOnOliver/skillshub

Build, scaffold, and deploy Power Automate cloud flows using the FlowStudio MCP server. 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

automate-this

25
from ComeOnOliver/skillshub

Analyze a screen recording of a manual process and produce targeted, working automation scripts. Extracts frames and audio narration from video files, reconstructs the step-by-step workflow, and proposes automation at multiple complexity levels using tools already installed on the user machine.

powershell-windows

25
from ComeOnOliver/skillshub

PowerShell Windows patterns. Critical pitfalls, operator syntax, error handling.