MCP YouTube Transcript
An MCP server retrieving transcripts of YouTube videos
Beschreibung vom Entwickler (englisches Original)
Competitive intelligence and brand monitoring for AI assistants via Watchr.
Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.
Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.
Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.
Du brauchst
Welche App nutzt du?
Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.
Funktioniert in Claude im Web, auf dem Desktop und auf dem Handy:
https://mcp.watchr.ai/mcpFühre das in deinem Terminal aus
claude mcp add --transport http watchr https://mcp.watchr.ai/mcpIn .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"watchr": {
"url": "https://mcp.watchr.ai/mcp"
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
In .vscode/mcp.json in deinem Projekt einfügen
{
"servers": {
"watchr": {
"type": "http",
"url": "https://mcp.watchr.ai/mcp"
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
ChatGPT verbindet sich nur mit Servern im Internet:
https://mcp.watchr.ai/mcpMenünamen können sich je nach Tarif und mit der Zeit leicht unterscheiden.
Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.
Diese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.
Der Server verlangt eine Anmeldung, bevor er seine Tools auflistet.
Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 7. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto getwatchr bestätigt, dem das Repo gehört
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieses Repo haben wir noch nicht von GitHub gelesen
Antwort in 826 ms (HTTP 401)
Gibt OAuth-Anmeldung an, damit deine KI-App dich zum Einloggen weiterleiten kann
Noch nicht geprüft; wir lesen die Tool-Liste, wenn wir den Endpunkt prüfen
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
Er hat 3 von 3 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.
Die Registry nennt keinen erforderlichen Schlüssel, manche Server bitten dich aber bei der ersten Nutzung, dich anzumelden.
Er läuft in der Cloud des Entwicklers. Du verbindest dich übers Internet, ohne etwas zu installieren, aber was du sendest, läuft über die Server des Entwicklers.
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (1.0.0) kam vor 5 Tagen in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Er verbindet sich per URL, also funktionieren auch Apps, die Remote-MCP-Server akzeptieren, zum Beispiel ChatGPT im Entwicklermodus.
In derselben Kategorie: MCP YouTube Transcript, Google Analytics MCP, BibiGPT YouTube Video Summarizer
Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.
So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti
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.
Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.
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:
Nur der Anfang wird gezeigt; den Rest findest du im Repo