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YouTube as a research engine: keyless search, video intel, resilient transcripts, demand signals.
About
YouTube as a research engine: keyless search, video intel, resilient transcripts, demand signals.
Security Report
Valid MCP server (3 strong, 3 medium validity signals). No known CVEs in dependencies. Package registry verified. Imported from the Official MCP Registry.
12 files analyzed ยท 1 issue found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
Permissions Required
This plugin requests these system permissions. Most are normal for its category.
How to Install
Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-not0lucky-tubescout": {
"args": [
"-y",
"tubescout"
],
"command": "npx"
}
}
}Documentation
View on GitHubFrom the project's GitHub README.
TubeScout ๐ญ
Turn YouTube into a research engine for your AI agent. An MCP server (no API key) plus a skill pack that make Claude Code, Codex, and OpenCode search YouTube like a database, read transcripts at scale, and mine videos for evidence โ claims, numbers, demand signals โ instead of vibes.
Idea-engine tools scan Reddit and forums. YouTube is where founders show receipts โ revenue dashboards, playbooks, real numbers on camera โ and nothing mines it. TubeScout does.
Quickstart (60 seconds)
Claude Code
claude mcp add --scope user tubescout -- npx -y tubescout
Codex
codex mcp add tubescout -- npx -y tubescout
OpenCode โ add to ~/.config/opencode/opencode.json under "mcp":
"tubescout": { "type": "local", "command": ["npx", "-y", "tubescout"], "enabled": true }
That's it โ no API key, no config. Then ask your agent things like:
"Find the 5 most-viewed videos about n8n from the last month and summarize what people are struggling with."
Easiest all-in-one (Claude Code): install as a plugin โ MCP server + all 6 skills in two commands:
/plugin marketplace add not0lucky/tubescout
/plugin install tubescout@tubescout
Or install the skill pack manually (works for Claude Code, Codex, and OpenCode):
git clone https://github.com/not0lucky/tubescout && cd tubescout
./scripts/install-skills.sh # installs into ~/.claude/skills, ~/.codex/skills, ~/.config/opencode/skills
Tools
| Tool | What it does |
|---|---|
search_videos | Search with filters (upload window, duration, sort by views/date) |
get_video | Full metadata + engagement (likesPer1kViews resonance signal) |
get_transcript | Plain-text transcript via a resilient 3-strategy fallback chain |
get_transcripts | Batch transcripts (up to 10 videos), per-video error tolerant |
get_channel_videos | Channel positioning + recent uploads with view counts |
get_search_suggestions | YouTube autocomplete = real search demand for keyword research |
Skills (the research methods)
| Skill | Use it to |
|---|---|
/yt-breakdown <urls> | Skeptic's analysis of videos: extract every claim and number, stress-test for incentives, survivorship bias, verifiability |
/yt-idea-mine <niche> | Mine a niche for product ideas backed by demand signals + pains real builders describe on camera |
/yt-validate <idea> | Go/no-go verdict: demand, saturation, what competitors' numbers actually show |
/yt-channel-intel <channel> | Read a channel's strategy: cadence, outliers, what performs vs what they publish |
/yt-playbook <tutorial url> | Turn a tutorial into executable steps โ exact commands, settings, and the gotchas said in passing โ adapted to your stack |
/yt-gap <niche> | Find demand-vs-supply gaps: heavily searched topics served by weak, old, or misfit videos โ for content plans or product angles |
All skills are context-aware: they read the conversation for what you're building, your stack, and videos already analyzed, and tailor verdicts to your actual leverage instead of giving generic advice.
See a real /yt-breakdown run on three "how I make $X/month" videos โ including what survived the skeptic pass and what didn't.
How it works (honestly)
There's no magic here, and that's the point:
- youtubei.js talks to YouTube's internal InnerTube API โ the same one the site uses. No key, no quota.
- Transcripts are YouTube's own captions, fetched through a fallback chain: the ANDROID-client timedtext track โ the InnerTube transcript endpoint (known to 400 intermittently โ retried with backoff) โ local
yt-dlpif you have it. Each response tells you whichsourceserved it. - All analysis happens in your agent. The server ships data; the skills ship method.
Limitations
- Run it locally. YouTube aggressively rate-limits datacenter IPs โ this is a local stdio server by design, not a hosted service.
- YouTube changes internals without notice; when it breaks, update (
npxalways pulls latest) and file an issue with the failing video ID. - Videos with captions disabled can't be transcribed (rare; the error says so explicitly).
- Caption scraping lives in YouTube ToS gray area โ fine for local research tooling, don't build a hosted paid product on it.
Development
npm install && npm run build
npm test # unit tests (offline)
npm run test:live # live smoke tests against real videos โ run before publishing
npm run inspect # MCP Inspector against the built server
MIT โ see LICENSE.
Built by Anir โ I automate things. More at agramprojects.com.
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