MCP YouTube Transcript
An MCP server retrieving transcripts of YouTube videos
Description from the maker (original English)
Triage failing DeviceCloud Maestro test runs: fail reasons, screenshots, flaky-flow analytics
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
DEVICE_CLOUD_API_KEYValues marked secret are keys to your account. Never share them or paste them into a chat.
You need
Which app do you use?
Pick your app above. We remember it, so next time the button says “Install in …”.
Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"devicecloud": {
"command": "npx",
"args": [
"-y",
"devicecloud-mcp"
],
"env": {
"DEVICE_CLOUD_API_KEY": "your-value"
}
}
}
}Run this in your terminal
claude mcp add devicecloud --env DEVICE_CLOUD_API_KEY=your-value -- npx -y devicecloud-mcpFill in the empty values before running it.
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"devicecloud": {
"command": "npx",
"args": [
"-y",
"devicecloud-mcp"
],
"env": {
"DEVICE_CLOUD_API_KEY": "your-value"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"devicecloud": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"devicecloud-mcp"
],
"env": {
"DEVICE_CLOUD_API_KEY": "your-value"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.
Your choice stays on this device in a cookie; no account needed.
These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026
The registry name was verified with the GitHub account RubenGlez, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
You need to fill in: DEVICE_CLOUD_API_KEY
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (0.3.2) reached the registry 3 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.
In the same category: MCP YouTube Transcript, Google Analytics MCP, BibiGPT YouTube Video Summarizer
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
An MCP server retrieving transcripts of YouTube videos
GA4 MCP server for AI agents: schema discovery, server-side aggregation, analysis-ready defaults.
AI video summarizer: summarize and transcribe YouTube, Bilibili, TikTok and podcast videos.
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
Triage failing DeviceCloud runs so your agent can fix them, without opening the dashboard.
When a DeviceCloud run goes red in CI, the reason why is buried in the web dashboard: the fail reason, the failure screenshot, the logs. This server pulls all of it straight into your editor, so your AI assistant (Claude Code, Cursor, Claude Desktop, etc.) can read the evidence, find the root cause, and fix the flow or app code. You commit, CI re-runs, and the dashboard stays closed.
DeviceCloud is a platform for running Maestro flows on real devices. Your CI triggers the runs; this server is how you debug the ones that fail.
It lets the assistant:
failReason for any uploadThe server is read-only against the DeviceCloud REST API: no dcd CLI dependency, and nothing an agent does can trigger billable runs. Triggering and re-running tests stay with your CI; cancelling a run stays in the dashboard.
Requires Node.js 22+ — check with node --version. There's no separate install step; the server runs on demand via npx.
Add this to your MCP client config:
{
"mcpServers": { "devicecloud": { "command": "npx", "args": ["-y", "devicecloud-mcp"], "env": { "DEVICE_CLOUD_API_KEY": " " } } } }
Get your API key at console.devicecloud.dev/settings.
Skip editing JSON — register the server in one step:
claude mcp add devicecloud --env DEVICE_CLOUD_API_KEY=<your-key> -- npx -y devicecloud-mcp
Add -s user to make it available in every project instead of only the current one.
The config block above is the same for every client; only the file location differs.
.mcp.json)Add to a .mcp.json at the root of any project where you want the tools available:
{
"mcpServers": { "devicecloud": { "command": "npx", "args": ["-y", "devicecloud-mcp"], "env": { "DEVICE_CLOUD_API_KEY": "${DEVICE_CLOUD_API_KEY}" } } } }
Then export the key from your shell profile so Claude Code's child process inherits it:
# ~/.zshrc or ~/.bashrc
export DEVICE_CLOUD_API_KEY=" "
Setting it only in an interactive shell isn't enough; Claude Code spawns the MCP from its own environment, so the variable needs to be in the profile.
~/.claude.json)If you want it available everywhere instead of per-project, add the same devicecloud block under mcpServers in ~/.claude.json.
Edit ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows). Restart Claude Desktop after saving; a tools icon appears in the chat input once the server connects.
Add to ~/.cursor/mcp.json (global) or .cursor/mcp.json at the project root (project-scoped).
Edit ~/.codeium/windsurf/mcp_config.json.
Any client that supports stdio MCP servers uses the same { command, args, env } shape. Consult the client's docs for the config file location.
Note: OpenAI products (ChatGPT, Codex, the Assistants API) use their own tool protocol and do not support MCP servers.
After restarting your assistant:
List recent DeviceCloud uploads, limit 3.
You should see a JSON-shaped response with an uploads array. If instead you get DEVICE_CLOUD_API_KEY env var is required, the variable isn't reaching the spawned process; re-check that it's exported from your shell profile (not just the current shell).
| Tool | Purpose |
|---|---|
diagnose_run | Start here. One-call triage of a run (uploadId or name): folds retries per flow and returns failed flows with fail reasons, durations, and auto-downloaded failure-screenshot paths, plus a passed/failed/flaky summary and suggested next steps. Set includeReport: false to skip the screenshot download; outputDir sets where the report extracts (default /tmp). |
suite_health | Classify every flow over a lookback window into healthy, flaky, broken, or regression, ranked worst-first, so you can tell whether a failure is worth fixing before diving in. Regressions (passing, then recently failing) come first. Same filters as list_flow_analytics (platform, appId, days, startDate, endDate, tags). |
list_uploads | List recent uploads. Filter by name (* wildcard), from, to, limit, offset. |
get_upload_status | Overall status + per-test status, duration, failReason. Provide uploadId or name. |
get_results | Per-flow rows for one upload: id, test_file_name, status, fail_reason, duration_seconds, retry_of. Optional client-side status filter. |
get_junit_report | Raw JUnit XML for an upload. |
get_html_report | Downloads + auto-unzips the HTML report. Returns the extraction dir and an inventory with failureScreenshots[] highlighted (these are the highest-signal debugging artifact). |
download_artifacts | Zip of raw artifacts (logs, screenshots, video). results: "FAILED" (default) or "ALL". Saves to /tmp by default; not auto-unzipped. |
list_flow_analytics | Per-flow pass rate, run counts, avg duration over a lookback window (default 14 days). Useful to tell flakes from genuinely-broken flows. |
get_flow_runs | Individual run history for one flow file (fileName required). Returns status, duration, failReason, and the uploadId each run belongs to. Use to drill into a specific flow after list_flow_analytics. |
Uploads are typically named after the commit or build that triggered them. A common convention is to include the short SHA:
fix(login): handle expired session (a1b2c3d4)
Filter with name = "*a1b2c3d4*" to find every upload for a specific commit. The wildcard is *, not %.
DeviceCloud uploads are created when you trigger a run, via the CLI, a CI step, the GitHub Action, or the API directly. Whether a given commit has an upload depends entirely on your CI setup. If list_uploads returns nothing for a SHA you expect, the run probably wasn't triggered for that commit.
~/.zshrc / ~/.bashrc, restart your assistant.get_html_report): the unzip binary is missing or crashed. Install with brew install unzip (macOS ships with it; Linux usually does too).