MCP YouTube Transcript
An MCP server retrieving transcripts of YouTube videos
제작자가 쓴 설명(영어 원문)
Per-URL SEO verdicts from GSC, GA4, Matomo, Clarity, AI citations: refresh/expand/merge/kill.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
GSC_SERVICE_ACCOUNT_JSON, GSC_SITE_URL, MATOMO_URL, MATOMO_TOKEN, MATOMO_SITE_ID, GA4_PROPERTY_ID, GA4_SERVICE_ACCOUNT_JSON, CLARITY_PROJECT_ID, CLARITY_API_TOKEN, POSTS_SITEMAP_URL, POSTS_LIST, GHOST_ADMIN_API_URL, GHOST_ADMIN_API_KEY, CITATION_INTELLIGENCE_URL비밀로 표시된 값은 내 계정의 열쇠예요. 절대 다른 사람과 공유하거나 채팅에 붙여 넣지 마세요.
필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"seo-performance": {
"command": "npx",
"args": [
"-y",
"@automatelab/seo-performance-mcp"
],
"env": {
"GSC_SERVICE_ACCOUNT_JSON": "your-value",
"GSC_SITE_URL": "your-value",
"MATOMO_URL": "your-value",
"MATOMO_TOKEN": "your-value",
"MATOMO_SITE_ID": "your-value",
"GA4_PROPERTY_ID": "your-value",
"GA4_SERVICE_ACCOUNT_JSON": "your-value",
"CLARITY_PROJECT_ID": "your-value",
"CLARITY_API_TOKEN": "your-value",
"POSTS_SITEMAP_URL": "your-value",
"POSTS_LIST": "your-value",
"GHOST_ADMIN_API_URL": "your-value",
"GHOST_ADMIN_API_KEY": "your-value",
"CITATION_INTELLIGENCE_URL": "your-value"
}
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add seo-performance --env GSC_SERVICE_ACCOUNT_JSON=your-value --env GSC_SITE_URL=your-value --env MATOMO_URL=your-value --env MATOMO_TOKEN=your-value --env MATOMO_SITE_ID=your-value --env GA4_PROPERTY_ID=your-value --env GA4_SERVICE_ACCOUNT_JSON=your-value --env CLARITY_PROJECT_ID=your-value --env CLARITY_API_TOKEN=your-value --env POSTS_SITEMAP_URL=your-value --env POSTS_LIST=your-value --env GHOST_ADMIN_API_URL=your-value --env GHOST_ADMIN_API_KEY=your-value --env CITATION_INTELLIGENCE_URL=your-value -- npx -y @automatelab/seo-performance-mcp실행하기 전에 빈 값을 채워 주세요.
프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"seo-performance": {
"command": "npx",
"args": [
"-y",
"@automatelab/seo-performance-mcp"
],
"env": {
"GSC_SERVICE_ACCOUNT_JSON": "your-value",
"GSC_SITE_URL": "your-value",
"MATOMO_URL": "your-value",
"MATOMO_TOKEN": "your-value",
"MATOMO_SITE_ID": "your-value",
"GA4_PROPERTY_ID": "your-value",
"GA4_SERVICE_ACCOUNT_JSON": "your-value",
"CLARITY_PROJECT_ID": "your-value",
"CLARITY_API_TOKEN": "your-value",
"POSTS_SITEMAP_URL": "your-value",
"POSTS_LIST": "your-value",
"GHOST_ADMIN_API_URL": "your-value",
"GHOST_ADMIN_API_KEY": "your-value",
"CITATION_INTELLIGENCE_URL": "your-value"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"seo-performance": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@automatelab/seo-performance-mcp"
],
"env": {
"GSC_SERVICE_ACCOUNT_JSON": "your-value",
"GSC_SITE_URL": "your-value",
"MATOMO_URL": "your-value",
"MATOMO_TOKEN": "your-value",
"MATOMO_SITE_ID": "your-value",
"GA4_PROPERTY_ID": "your-value",
"GA4_SERVICE_ACCOUNT_JSON": "your-value",
"CLARITY_PROJECT_ID": "your-value",
"CLARITY_API_TOKEN": "your-value",
"POSTS_SITEMAP_URL": "your-value",
"POSTS_LIST": "your-value",
"GHOST_ADMIN_API_URL": "your-value",
"GHOST_ADMIN_API_KEY": "your-value",
"CITATION_INTELLIGENCE_URL": "your-value"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
GSC_SITE_URL envMATOMO_URL envMATOMO_SITE_ID envGA4_PROPERTY_ID envCLARITY_PROJECT_ID envPOSTS_SITEMAP_URL envPOSTS_LIST envGHOST_ADMIN_API_URL envCITATION_INTELLIGENCE_URL env이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 7일 점검
레지스트리 이름이 GitHub 계정 AutomateLab-tech 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
입력해야 할 값: GSC_SERVICE_ACCOUNT_JSON, MATOMO_TOKEN, GA4_SERVICE_ACCOUNT_JSON, CLARITY_API_TOKEN, GHOST_ADMIN_API_KEY
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(1.0.1)은 11일 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Node.js도 있어야 해요.
같은 카테고리에는: MCP YouTube Transcript, Google Analytics MCP, BibiGPT YouTube Video Summarizer
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
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.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
Know which blog posts to refresh, expand, merge, or kill - without guessing.
A MCP server that turns your scattered SEO and analytics data into one clear verdict per URL. Plug it into Claude, Cursor, or any MCP-aware client and ask: "Which three posts should I update this week?" - and get an answer backed by hard numbers.
seo-performance-mcp unifies post-publish signals from every channel you already pay for:
It then runs a deterministic rule engine over those signals and emits a verdict per URL:
refresh/expand/merge/kill/double_down/hold
with reason codes, evidence, and a 0-1 confidence score. Reporting only - the server never mutates your posts.
Most content teams have analytics in five tabs and a gut feeling. That's how good posts rot quietly, mediocre posts get over-promoted, and the obvious "rewrite this one" is invisible until traffic has already cratered.
This MCP closes the loop:
src/verdict/rules.ts.After one cohort run you have:
npx -y @automatelab/seo-performance-mcp
In a Claude, Claude Code, or Cursor MCP config:
{
"mcpServers": { "seo-performance": { "command": "npx", "args": ["-y", "@automatelab/seo-performance-mcp"], "env": { "POSTS_SITEMAP_URL": "https://example.com/sitemap.xml", "GSC_SERVICE_ACCOUNT_JSON": " ", "GSC_SITE_URL": "sc-domain:example.com", "MATOMO_URL": "https://example.com/analytics", "MATOMO_TOKEN": "...", "MATOMO_SITE_ID": "1", "GA4_PROPERTY_ID": "123456789", "GA4_SERVICE_ACCOUNT_JSON": " ", "CLARITY_PROJECT_ID": "...", "CLARITY_API_TOKEN": "...", "CITATION_INTELLIGENCE_URL": "https://citation.example.com" } } } }
Every env var is optional. Adapters that lack their env config skip their slice of the snapshot; the server still boots. The verdict engine works on whatever slices are present.
Point it at any site, no CMS plugin required. The post-discovery layer resolves in priority order:
{url, title?, published_at?, tags?, word_count?}. Use this when you already have a content index and want exact control.GHOST_ADMIN_API_URL and GHOST_ADMIN_API_KEY are set, Ghost is used as a richer metadata source. Optional.og:title, article:published_time, and JSON-LD datePublished are read live from the URL.POSTS_SITEMAP_URL to your sitemap (or sitemap index) and the server enumerates posts from + .Most users only need POSTS_SITEMAP_URL. WordPress, Hugo, Astro, Next.js, Webflow, Framer, Wix, Squarespace, Notion-as-a-site, Substack-mirror sites all expose a sitemap by default.
To add a brand-new platform: nothing to build - just point POSTS_SITEMAP_URL at it.
| Tool | What it returns |
|---|---|
posts_list | Posts with {url, title, age_days, tags} from sitemap, Ghost, or your POSTS_LIST. |
posts_snapshot | Per-URL unified rollup for a 30/60/90-day window: GSC + Matomo + GA4 + Clarity + citations + meta. |
posts_decay_curve | Weekly GSC clicks/impressions/position buckets + a decay/plateau/growth trend label. |
posts_verdict | Verdict (refresh/expand/merge/kill/double_down/hold) + reason codes + 0-1 confidence. |
posts_refresh_brief | Markdown brief for a human or downstream LLM editor: numbers, top queries, suggested actions. |
cohort_report | Cohort verdict table sorted by priority + confidence. "Which three posts should I refresh this week?" |
posts_cite_loss | LLM citations that dropped off for a given URL. Needs CITATION_INTELLIGENCE_URL. |
gsc_quick_wins | (page, query) pairs at positions 5-15 with low CTR - fastest title-rewrite wins. |
Run any of the tools on a cron from CI and post the output to a GitHub Issue, Discussion, or PR. The action is published on the GitHub Marketplace.
- uses: AutomateLab-tech/seo-performance-mcp@v1
with: tool: cohort_report format: markdown input: '{"window": 90, "min_age_days": 90, "limit": 20}' gsc-service-account-json: ${{ secrets.GSC_SERVICE_ACCOUNT_JSON }} gsc-site-url: ${{ secrets.GSC_SITE_URL }} posts-sitemap-url: ${{ secrets.POSTS_SITEMAP_URL }}
Outputs:
| Output | Description |
|---|---|
result | Tool output as a multi-line string (markdown or JSON, per format). |
result-file | Path of the file the tool output was written to. Hand to peter-evans/create-issue-from-file etc. |
rows | For cohort_report with format: json only: number of rows returned. |
A complete weekly-audit workflow that opens a GitHub Issue with the cohort report is in examples/weekly-cohort-report.yml.
The package also ships a seo-perf-cli bin so you can run a single tool without an MCP client:
npx -p @automatelab/seo-performance-mcp seo-perf-cli cohort_report \
--input '{"window": 90, "limit": 20}' \ --format markdown
Same env vars as the MCP server. --format markdown is supported for cohort_report and posts_refresh_brief; other tools fall back to fenced JSON.
Three thin routing files ship in the repo so the LLM in your client knows *when* to reach for these tools:
skills/seo-performance/SKILL.md - tool-routing skill. Drop into ~/.claude/skills/seo-performance/ (or .claude/skills/ per project) to auto-load in Claude Code. Routes a single question to the right tool.skills/weekly-audit/SKILL.md - one-shot weekly audit playbook. Composes gsc_quick_wins + cohort_report + posts_cite_loss into a deduped, cross-signal ranked digest with proposed edits per URL. Drop in alongside the routing skill.cursor/rules/seo-performance.mdc - copy to .cursor/rules/seo-performance.mdc in any Cursor workspace.All optional. The MCP server works without them; they just shorten the "which tool do I call" round-trip.
The server exposes three prompts that bundle the playbook. Any MCP client (Claude Desktop, Claude Code, Cursor, Continue) can list and invoke them:
| Prompt | What it runs |
|---|---|
audit_cohort | cohort_report on posts >=90d, then posts_refresh_brief per refresh/expand/merge row. The weekly audit. |
find_quick_wins | gsc_quick_wins (positions 5-15) + per-URL posts_snapshot, then proposes verbatim-query meta_title rewrites. |
citation_loss_sweep | posts_cite_loss per URL, refresh_brief for any with losses, targeted H1/lead phrasing recommendations. |
Deterministic, rule-based, traceable. Reason codes:
ctr_below_position_expectedposition_driftdecay_30d_over_30pct / decay_60d_over_50pctstagnant_no_clicksthin_content_low_dwellrising_impressions_low_ctr / rising_clicks_continue_investmentcitation_loss / citation_growthduplicate_or_cannibalizinghigh_bounce_low_scrollfresh_post_too_youngThe mapping (reasons → verdict) and every threshold lives in src/verdict/rules.ts. Edit it, pin it in tests, ship your own rule book.
npm install
npm run dev # tsx src/index.ts npm run build # tsc npm test # vitest
MIT
See the maintenance guide for interpretation limits, current tool names where applicable, and reproducible verification.