MCP YouTube Transcript
An MCP server retrieving transcripts of YouTube videos
Descripción del creador (original en inglés)
Competitive intelligence and brand monitoring for AI assistants via Watchr.
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
Elige la app de IA que usas y copia la configuración.
Necesitas
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Funciona en Claude para web, escritorio y móvil:
https://mcp.watchr.ai/mcpEjecuta esto en tu terminal
claude mcp add --transport http watchr https://mcp.watchr.ai/mcpPégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"watchr": {
"url": "https://mcp.watchr.ai/mcp"
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"watchr": {
"type": "http",
"url": "https://mcp.watchr.ai/mcp"
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
ChatGPT solo se conecta a servidores en internet:
https://mcp.watchr.ai/mcpLos nombres de los menús pueden variar un poco según el plan y con el tiempo.
Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.
Esta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
El servidor pide iniciar sesión antes de mostrar sus herramientas.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 8 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub getwatchr, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Respondió en 826 ms (HTTP 401)
Declara inicio de sesión con OAuth, así que tu app de IA puede llevarte a iniciar sesión
Aún sin revisar; leemos la lista de herramientas cuando revisamos el endpoint
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
Superó 3 de 3 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.
El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.
Se ejecuta en la nube del creador. Te conectas por internet sin instalar nada, pero lo que envías pasa por los servidores del creador.
El repo de GitHub cambió por última vez –, y la última versión (1.0.0) llegó al registro hace 5 días.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. Se conecta por URL, así que también funcionan las apps que aceptan servidores MCP remotos, como ChatGPT en modo desarrollador.
En la misma categoría: MCP YouTube Transcript, Google Analytics MCP, BibiGPT YouTube Video Summarizer
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
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.
Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.
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:
Solo se muestra el principio; lee el resto en el repo