Flowstudio Power Automate MCP

What it does

When your agent uses it

• Tasks that involve MCP servers

Example prompts

• “/flowstudio-power-automate-mcp”

Requirements

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

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

1. 1Extract, don't echo. Pull the specific field(s) you need (one operationId, one action's outputs) and discard the rest before reasoning…
2. 2Always pass actionName to get_live_flow_run_action_outputs. Omitting it fetches all top-level actions. For actions inside a foreach…
3. 3Reuse the spill file within a session. Refetching the same connector swagger costs 30+ seconds and produces another spill — cache the path.
4. 4Don't grep the spill file for JSON keys directly. Strings are JSON-escaped inside the file (\"OperationId\":), so a plain grep for…
5. 5Summarize tool output to the user. Echo name + state + trigger for flow lists and actionName + status + code for run errors — not raw…

What it can do on your machine

Read from SKILL.md and the folder at commit 727ff2e. 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

  Also links to:

  • github.com
  • learn.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

Flowstudio Power Automate MCP loads about 3.4k tokens when it runs, and up to ~11k if it reads all its reference files. Until then it costs about 168 tokens; SKILL.md has 1,192 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~168

When it runs · the whole SKILL.md, loaded when a task matches

~3.4k

With references · SKILL.md plus every file in references/, read only if the agent opens them

~11k

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

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 github/awesome-copilot at commit 727ff2e, republished under its MIT licence (© github). 1,192 words, ~3,429 tokens.

name

flowstudio-power-automate-mcp

description

Foundation skill for Power Automate via FlowStudio MCP — auth setup, the reusable MCP helper (Python + Node.js), tool discovery via `list_skills` / `tool_search`, and oversized-response handling. Load this skill first when connecting an agent to Power Automate. For specialized workflows, load `flowstudio-power-automate-build`, `flowstudio-power-automate-debug`, `flowstudio-power-automate-monitoring` (Pro+), or `flowstudio-power-automate-governance` (Pro+) — each contains the workflow narrative, this skill provides the plumbing they all rely on. Requires a FlowStudio MCP subscription or compatible server — see https://mcp.flowstudio.app

# Cold start — pick a bundle by intent
skills = mcp("list_skills", {})
# [{"name": "debug-flow", "description": "Investigate why a flow is failing...",
#   "tools": ["get_live_flow_runs", "get_live_flow_run_error", ...]}, ...]

# Load schemas for the bundle
debug_tools = mcp("tool_search", {"query": "skill:debug-flow"})

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)

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);
}

skills = mcp("list_skills", {})
print(f"Connected — {len(skills)} skill bundles available:",
      [s["name"] for s in skills])

Connected — 6 skill bundles available: ['build-flow', 'create-flow', 'debug-flow', 'monitor-flow', 'discover', 'governance']

[{"type":"text","text":"<JSON-escaped payload>"}]

import json
with open(path) as f:
    raw = json.loads(f.read())
payload = json.loads(raw[0]["text"])

$payload = ((Get-Content $path -Raw | ConvertFrom-Json)[0].text) | ConvertFrom-Json

# Good — drill into one operation in a connector swagger
conn = mcp("describe_live_connector", {"environmentName": ENV, "connectorName": "shared_sharepointonline"})
op = conn["properties"]["swagger"]["paths"]["/datasets/{dataset}/tables/{table}/items"]["get"]
print(op["operationId"], "—", op.get("summary"))

# Bad — keeping the whole 500 KB swagger in context
print(json.dumps(conn, indent=2))   # don't do this

© github, 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 4 other files (references) in skills/flowstudio-power-automate-mcp of github/awesome-copilot.

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

Open the folder on GitHubat commit 727ff2e

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in github/awesome-copilot, which our catalogue first saw on October 7, 2026.

• boshi-xixixi/TraeSkill.trae/Skills/.agents/skills/flowstudio-power-automate-mcp