Agent skill

Power Automate MCP

by LeoYeAI in LeoYeAI/openclaw-master-skills

Connect to and operate Power Automate cloud flows via a FlowStudio MCP server.

MITAuto-check passedAgent Workflows

Install Power Automate MCP

skills CLI
$ npx skills add LeoYeAI/openclaw-master-skills --skill power-automate-mcp -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install LeoYeAI/openclaw-master-skills power-automate-mcp --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/power-automate-mcp .claude/skills/power-automate-mcp && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
power-automate-mcp
GitHub stars
2.2k
Token cost
~4.4k tokens
SKILL.md length
1,073 words
Files
6 (incl. references)
Skills in repo
1,235
Repo updated
First seen
Licence
MIT

At a glance

Connect to and operate Power Automate cloud flows via a FlowStudio MCP server.

  • Asked to: list flows
  • SKILL.md covers Source of Truth, Recommended Language: Python…, What You Can Do and Which Tool Tier to Call First, plus 14 more sections
  • Calls pip; reaches mcp.flowstudio.app
  • Read a flow definition

What it does

Power Automate MCP is an agent skill from LeoYeAI/openclaw-master-skills. 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 —…

Its SKILL.md is about 4.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including reference files (for example `_meta.json`, `references/MCP-BOOTSTRAP.md` and `references/action-types.md`).

It sits in Agent Workflows, covering MCP servers. It works with Model Context Protocol, Power Automate, Python and Node.js. The repository describes itself as: 🧠 Curated collection of 1209+ best OpenClaw skills — weekly updated by MyClaw.ai. The licence is MIT.

When your agent uses it

  • Asked to: list flows
  • Read a flow definition
  • Check run history
  • Inspect action outputs

Example prompts

  • “/power-automate-mcp”

Requirements

  • Python 3
  • Node.js
  • A credential in FLOWSTUDIO_MCP_TOKEN
  • A credential in YOUR_JWT_TOKEN

What it can do on your machine

Read from SKILL.md and the folder at commit e5199b5. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • pip

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • mcp.flowstudio.app

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Power Automate MCP loads about 4.4k tokens when it runs, and up to ~9.9k if it reads all its reference files. Until then it costs about 142 tokens; SKILL.md has 1,073 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~142
When it runs · the whole SKILL.md, loaded when a task matches
~4.4k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~9.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from LeoYeAI/openclaw-master-skills at commit e5199b5, republished under its MIT licence (© LeoYeAI). 1,073 words, ~4,366 tokens.

Download SKILL.mdSave it as .claude/skills/power-automate-mcp/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.
name
power-automate-mcp
description
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

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

PrioritySourceCovers
1Real API responseAlways trust what the server actually returns
2tools/listTool names, parameter names, types, required flags
3SKILL docs & reference filesResponse 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.


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.

LanguageVerdictNotes
Python✅ RecommendedClean JSON handling, no escaping issues, all skill examples use it
Node.js (≥ 18)✅ RecommendedNative fetch + JSON.stringify/JSON.parse; async/await fits MCP call patterns well; no extra packages needed
PowerShell⚠️ Avoid for flow operationsConvertTo-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 fragileShell-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
ToolWhat it does
list_live_flowsList flows in an environment directly from the PA API (always current)
list_live_environmentsList all Power Platform environments visible to the service account
list_live_connectionsList all connections in an environment from the PA API
get_live_flowFetch the complete flow definition (triggers, actions, parameters)
get_live_flow_http_schemaInspect the JSON body schema and response schemas of an HTTP-triggered flow
get_live_flow_trigger_urlGet the current signed callback URL for an HTTP-triggered flow
trigger_live_flowPOST to an HTTP-triggered flow's callback URL (AAD auth handled automatically)
update_live_flowCreate a new flow or patch an existing definition in one call
add_live_flow_to_solutionMigrate a non-solution flow into a solution
get_live_flow_runsList recent run history with status, start/end times, and errors
get_live_flow_run_errorGet structured error details (per-action) for a failed run
get_live_flow_run_action_outputsInspect inputs/outputs of any action (or every foreach iteration) in a run
resubmit_live_flow_runRe-run a failed or cancelled run using its original trigger payload
cancel_live_flow_runCancel 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.

ToolWhat it does
list_store_flowsSearch flows from the cache with governance flags, run failure rates, and owner metadata
get_store_flowGet full cached details for a single flow including run stats and governance fields
get_store_flow_trigger_urlGet the trigger URL from the cache (instant, no PA API call)
get_store_flow_runsCached run history for the last N days with duration and remediation hints
get_store_flow_errorsCached failed-only runs with failed action names and remediation hints
get_store_flow_summaryAggregated stats: success rate, failure count, avg/max duration
set_store_flow_stateStart or stop a flow via the PA API and sync the result back to the store
update_store_flowUpdate governance metadata (description, tags, monitor flag, notification rules, business impact)
list_store_environmentsList all environments from the cache
list_store_makersList all makers (citizen developers) from the cache
get_store_makerGet a maker's flow/app counts and account status
list_store_power_appsList all Power Apps canvas apps from the cache
list_store_connectionsList all Power Platform connections from the cache

Show full SKILL.md (350 more words)Show less

Which Tool Tier to Call First

TaskToolNotes
List flowslist_live_flowsAlways current — calls PA API directly
Read a definitionget_live_flowAlways fetched live — not cached
Debug a failureget_live_flow_runs → get_live_flow_run_errorUse 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.
  • 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

FieldValue
Auth headerx-api-key: <JWT> — not Authorization: Bearer
Token formatPlain JWT — do not strip, alter, or prefix it
TimeoutUse ≥ 120 s for get_live_flow_run_action_outputs (large outputs)
Environment nameDefault-<tenant-guid> (find it via list_live_environments or list_live_flows response)

Reference Files


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.

© LeoYeAI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 5 other files (references) in skills/power-automate-mcp of LeoYeAI/openclaw-master-skills.

  • SKILL.md
  • _meta.json
  • references/MCP-BOOTSTRAP.md
  • references/action-types.md
  • references/connection-references.md
  • references/tool-reference.md

Open the folder on GitHubat commit e5199b5

Compare with similar skills

Power Automate MCP next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Power Automate MCP compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Power Automate MCP this skillLeoYeAI/openclaw-master-skills2.2k—~4.4kAutomated safety check: PassMIT
Flowstudio Power Automate MCPgithub/awesome-copilot40k1 repos~3.4kAutomated safety check: PassMIT
Power Automate MCPhashgraph-online/awesome-codex-plugins1.3k—~3.4kAutomated safety check: PassApache-2.0
Copilot SDKintellectronica/agent-skills295—~3.2kAutomated safety check: PassCC0-1.0
Copilot SDKaiskillstore/marketplace4334 repos~3.8kAutomated safety check: PassNone
Copilot SDKmicrosoft/skills3.1k—~7.1kAutomated safety check: PassMIT

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Categories

Questions about Power Automate MCP

What does Power Automate MCP do?

Connect to and operate Power Automate cloud flows via a FlowStudio MCP server. Power Automate MCP is an agent skill from LeoYeAI/openclaw-master-skills. Connect to and operate Power Automate cloud flows via a FlowStudio MCP server.

When should I use Power Automate MCP?

Power Automate MCP fits situations like: asked to: list flows; read a flow definition; check run history; inspect action outputs.

How do I install Power Automate MCP in Claude Code?

Run `npx skills add LeoYeAI/openclaw-master-skills --skill power-automate-mcp -a claude-code`. Or copy the skill folder (skills/power-automate-mcp in LeoYeAI/openclaw-master-skills) into .claude/skills/power-automate-mcp in your project. Claude Code loads it when a task matches its description.

How do I install Power Automate MCP in Codex?

Run `npx skills add LeoYeAI/openclaw-master-skills --skill power-automate-mcp -a codex`. Or copy the skill folder (skills/power-automate-mcp in LeoYeAI/openclaw-master-skills) into .agents/skills/power-automate-mcp in your project. Codex loads it when a task matches its description.

Can I use Power Automate MCP in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add LeoYeAI/openclaw-master-skills --skill power-automate-mcp -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/power-automate-mcp, .gemini/skills/power-automate-mcp, .github/skills/power-automate-mcp and .opencode/skills/power-automate-mcp in your project.

What does Power Automate MCP need to run?

Going by SKILL.md and its folder, Power Automate MCP needs the command-line tools its instructions call (pip). Our summary lists: Python 3; Node.js; A credential in FLOWSTUDIO_MCP_TOKEN; A credential in YOUR_JWT_TOKEN.

Does Power Automate MCP access the network?

SKILL.md names 1 domain. In commands or code: mcp.flowstudio.app; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Power Automate MCP safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Power Automate MCP use?

Power Automate MCP is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Power Automate MCP use?

About 4.4k tokens (SKILL.md is roughly 17k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 5.5k tokens, read only when the agent opens those files.

What are the alternatives to Power Automate MCP?

Skills that share tags, products or a category with Power Automate MCP: Flowstudio Power Automate MCP (github/awesome-copilot, 40k stars), Power Automate MCP (hashgraph-online/awesome-codex-plugins, 1.3k stars), Copilot SDK (intellectronica/agent-skills, 295 stars) and Copilot SDK (aiskillstore/marketplace, 433 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Power Automate MCP?

LeoYeAI (a GitHub user) maintains it in LeoYeAI/openclaw-master-skills, which has 2,161 GitHub stars. The repository holds 1,235 skills in this directory. The repository was last updated on July 20, 2026.

Source: LeoYeAI/openclaw-master-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.