MCP YouTube Transcript
An MCP server retrieving transcripts of YouTube videos
제작자가 쓴 설명(영어 원문)
Competitive intelligence and brand monitoring for AI assistants via Watchr.
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.
필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
웹, 데스크톱, 모바일의 Claude에서 쓸 수 있어요:
https://mcp.watchr.ai/mcp터미널에서 이 명령어를 실행하세요
claude mcp add --transport http watchr https://mcp.watchr.ai/mcp프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"watchr": {
"url": "https://mcp.watchr.ai/mcp"
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"watchr": {
"type": "http",
"url": "https://mcp.watchr.ai/mcp"
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요:
https://mcp.watchr.ai/mcp메뉴 이름은 요금제나 시기에 따라 조금 다를 수 있어요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
서버가 도구 목록을 보여 주기 전에 로그인을 요구해요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 8일 점검
레지스트리 이름이 GitHub 계정 getwatchr 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
826ms 만에 응답(HTTP 401)
OAuth 로그인을 지원한다고 밝혀서, AI 앱이 로그인 화면으로 안내해 줘요
아직 점검하지 않았어요. 엔드포인트를 점검할 때 도구 목록을 읽어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 3개 중 3개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
제작자의 클라우드에서 실행돼요. 설치 없이 인터넷으로 연결하지만, 보내는 내용은 제작자의 서버를 거쳐요.
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(1.0.0)은 5일 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. URL로 연결되기 때문에, 원격 MCP 서버를 지원하는 앱(예: 개발자 모드의 ChatGPT)에서도 쓸 수 있어요.
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.
Bring competitive intelligence and brand monitoring into your AI assistant. Ask Claude, Cursor, or any MCP-compatible client what your competitors did this week. Answers come straight from your Watchr workspace.
Watchr is a competitive intelligence and brand monitoring platform. It watches your competitors' websites, ads, social posts, news, and other sources, then qualifies each signal against a prompt you define, so what you see is *relevant* movement, not noise.
This repository documents the official Model Context Protocol (MCP) server for Watchr. It exposes account-scoped data and controlled account workflows. API keys provide read access; authorized OAuth administrators can also configure watchlists, manage members, record feedback and manage account tags.
The server is hosted by Watchr. No local install, no Docker. Just point your client at https://mcp.watchr.ai/mcp and authenticate. There are two paths, depending on your client:
Once connected, you can ask your AI assistant things like:
The MCP server provides the data; your assistant handles the reasoning, drafting, and integration with the rest of your workflow.
A short conversation with Claude pulling the latest HubSpot signals through Watchr:
Same data, one follow-up prompt later. Claude generates a designed competitive briefing artifact directly from the validated Watchr insights:
This is the core loop. Watchr collects and qualifies. Your AI client reasons and outputs. The MCP server is the glue.
The default endpoint exposes 37 tools, including reads and writes. The dedicated ChatGPT profile exposes 62 tools, with individually named configuration preview/apply actions. Runtime tools/list is the source of truth for arguments, schemas and permissions.
| Tool | Purpose |
|---|---|
list_monitoring_groups | List all monitoring groups (watchlists) you have access to. Each group bundles one or more tracked brands and a custom qualifying prompt that defines what counts as relevant. |
list_brands | List the competitor brands tracked inside a monitoring group. Use this to resolve brand names before searching. |
search_insights | Search validated insights with filters (brand, date range, source type, free-text). Returns a compact list designed to decide which insights to open. |
get_insight | Fetch the full body of a single insight by ID: source URL, original content, screenshots, qualifying rationale, dates, and related items when available. |
list_reports | List reports that have been sent from a monitoring group. |
get_report | Fetch the full body of a single report: narrative, included insights, recipients, send date. |
get_workspace_context | Read role, credential scopes, effective permissions and account limits. |
list_watchr_documentation | Discover product guides and supported capabilities. |
get_watchr_guide | Read a selected product guide. |
get_monitoring_configuration | Read brands, sources, goals, relevance and report settings. |
diagnose_monitoring | Read configuration diagnostics and recorded report counters when available. |
preview_monitoring_changes | Save a bounded configuration preview without applying it. |
apply_monitoring_changes | Apply the exact approved preview, rechecking permissions and entitlements. |
get_operation_status | Read operation progress, pending confirmation or partial failure. |
set_report_email_delivery | Preview the combined report-generation and email-delivery setting. |
list_workspace_members | Read account members and pending invitations. |
invite_workspace_member | Invite a member with an explicitly authorized role. |
revoke_workspace_invitation | Revoke an explicitly identified pending invitation. |
update_workspace_member_role | Change a member role, protecting the final administrator. |
remove_workspace_member | Remove member access and revoke corresponding connections. |
list_insight_tags | Read the account tag catalog, definitions and versions. |
check_insight_tag | Validate a proposed tag and expose overlap warnings without saving. |
save_insight_tag | Create, edit, archive or reactivate an account tag. |
update_insight_tags | Add, remove or replace tags on a bounded batch of insights. |
get_insight_tags | Read tags, manual exclusions and classification state for selected insights. |
get_insight_tag_history | Read the bounded tag correction and classification audit. |
create_insight_tag_job | Prepare an explicit classification job with IDs and budget limits. |
run_insight_tag_job | Advance a job by at most one external model call within its limits. |
get_insight_tag_job | Read job progress and reserved budget without running it. |
list_watchr_skills | Discover packaged methods and their resource files. |
get_watchr_skill | Read a packaged skill file. |
search_signals | Search watchlist-scoped topics and synchronize their changes. |
get_signal | Read a topic with paginated source and report references. |
search_rejected_insights | Search retained individual rejected sources and their reasons. |
get_rejected_insight | Read an accessible retained rejection with its original evidence. |
record_insight_feedback | Record an explicit relevance, homonym or duplicate judgment without hiding the source. |
list_insight_feedback | Read recorded judgments and their provenance. |
Collections support their documented pagination and filters. Configuration uses a persistent preview followed by explicit approval before application. Reads require mcp:read; configuration and tag writes additionally require mcp:configure; member administration requires mcp:members:manage. Current roles and permissions are checked server-side. API keys remain read-only.
Previewing does not start collection, send emails or apply a change. Some apply actions launch external discovery or collection. Tag definitions do not reclassify history: classification jobs are explicit, bounded and budgeted, and preserve manual corrections by default. Recorded relevance feedback does not change qualification or perform replay.
New MCP-created watchlists have report preparation and email delivery disabled by default. Those two effects share one setting; disabling it does not stop collection. Existing report preferences are preserved.
search_insights returns a compact discovery payload. Every item includes an id, a title, a factual summary, source and brand metadata, and an effective_date. The accompanying date_type says whether that effective date is the source publication date (published) or Watchr's detection date (detected). Website changes therefore remain safely dateable even when they have no publication date.
The search response intentionally omits the original description, qualification_analysis, raw dates, and related_items. This keeps result pages small enough for an AI client to rank and shortlist without spending its context window on source text it may never use.
When an item's title or summary is not clear enough, call get_insight with the returned id as insight_id before answering. get_insight provides the source description, qualification reasoning, published and detected dates, and any related validated insights. Consumers should not infer missing detail from the compact summary alone.
search_signals and get_signal expose watchlist-scoped topics, source relations and recorded report appearances. competitive_signal_id is a legacy shared grouping hint, not the authoritative topic identity. Historical report appearances may be unavailable when no structure was recorded. A stored snapshot timestamp is not proof of the actual screenshot capture time.
The Watchr onboarding skill helps an authorized assistant read your current setup, prepare a first watchlist or improve an existing one, show the exact preview, and verify the result after your approval. The skill and the MCP connection are separate: installing the skill does not grant access or change your account.
To install it for one project, copy the entire skills/watchr-onboarding/ directory from this repository to .claude/skills/watchr-onboarding/ for Claude Code or .agents/skills/watchr-onboarding/ for Codex. For a personal installation, use ~/.claude/skills/watchr-onboarding/ or ~/.agents/skills/watchr-onboarding/ respectively. Keep both SKILL.md and agents/openai.yaml together.
Connect Claude Code with claude mcp add --transport http watchr https://mcp.watchr.ai/mcp, then authorize through /mcp. Connect Codex with codex mcp add watchr --url https://mcp.watchr.ai/mcp/chatgpt, then run codex mcp login watchr. Complete Watchr sign-in only in the browser. Once connected, ask your assistant to use the Watchr onboarding skill.
If you start in Claude Code or Codex without a Watchr account, begin the MCP OAuth connection in that client. The browser opens Watchr's dedicated agent signup page from the validated authorization request, then returns to consent after account creation. The trial begins when the account is created; no watchlist or report email is enabled by signup alone. A direct visit to the page has no OAuth state. Real Claude Code and Codex onboarding with a new empty account still needs end-to-end acceptance testing.
You need a configured Watchr workspace before the MCP server has anything interesting to return. The full path:
앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요