MCP YouTube Transcript
An MCP server retrieving transcripts of YouTube videos
Descripción del creador (original en inglés)
Fantasy football analytics: stats, dynasty, projections, prospects, Sleeper leagues, Excel I/O
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 …”.
Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json
{
"mcpServers": {
"stathead": {
"command": "npx",
"args": [
"-y",
"stathead-mcp"
]
}
}
}Ejecuta esto en tu terminal
claude mcp add stathead -- npx -y stathead-mcpPégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"stathead": {
"command": "npx",
"args": [
"-y",
"stathead-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": {
"stathead": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"stathead-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.
Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.
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.
Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 6 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub dachhack, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Este se ejecuta en tu computadora; no hay endpoint en internet
Se ejecuta en tu computadora y usa ajustes locales en su lugar
Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet
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 1 de 1 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 tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).
El repo de GitHub cambió por última vez –, y la última versión (1.0.126) llegó al registro ayer.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Node.js en tu computadora.
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.
An MCP server that exposes StatHead's NFL fantasy-analytics toolset to Claude (Desktop / Code), Cursor, or any MCP client — so you can ask natural-language questions and get live, structured NFL data back.
It ships as a single self-contained bundle with no runtime dependencies and fetches all data on demand, so there's nothing to download or build — npx and go.
50 tools spanning player and team data, including:
| Area | Tools |
|---|---|
| Discovery | get_metadata — sources, season coverage, and valid enums (call this first to scope a question) |
| Players | season stats, weekly/game logs, snap counts, injuries, advanced stats, Next Gen Stats, rosters, contracts, get_depth_charts (slot-aware team depth charts with roster status, StatHead depth order and view=changes for moves) |
| Games & plays | schedules/results, play-by-play, participation, FTN charting |
| Fantasy | StatHead blended dynasty values, get_trade_values (StatHead values fitted to millions of completed Sleeper dynasty trades: as-of weekly values with 90% ranges, movers, liquidity, scoring re-pricing, 1/3/6/12-month forecasts, rookie-pick classes and history), get_projections (StatHead's in-house season PPG model), get_weekly_projections (per-week matchup-adjusted points, weeks 1–18), get_matchups (weekly strength of matchup: fantasy points each defense allows per game to QB/RB/WR/TE, ranked 1–32 in your scoring and over expected, by week, per player, rest of schedule, or split by metric such as TE receptions or QB rushing), ADP (FFC / ESPN / Sleeper), get_adp_with_results (ADP vs actual finish), trending adds/drops |
| Sleeper leagues | get_sleeper_user_leagues, get_sleeper_league (standings + rosters), get_sleeper_league_users (cheap manager list), get_sleeper_matchups, get_sleeper_transactions (trades/waivers/adds), get_sleeper_waiver_wire (free agents × trending × projections), get_sleeper_draft, get_sleeper_user_snooper (cross-league exposure), get_sleeper_user_history (multi-season records + titles) — a connected graph: a username lists leagues, a league name (or id) opens that league, and each manager's owner_id/display name walks back to *their* leagues, exposure, and history |
| Draft & college | get_prospect_outcomes (calibrated boom/bust probabilities + grades), draft picks, get_rookie_class (draft+combine+rookie stats in one call), prospect profiles, combine, college stats (player or cohort), QBR |
| Model & methodology | get_model_docs (how the models work + per-position feature importance), get_player_features (why a player is scored the way they are — feature drivers, bands, direction) |
| Your own numbers | export_excel / import_excel / clear_overrides — download a styled projections / rankings / rookie-rankings workbook (or a by_team projection sheet with live PPR formulas), edit it, re-upload it, and have your values drive every later query |
The same boards the website lets you download are available over MCP as real .xlsx files (built with zero extra dependencies — Node's own zlib):
export_excel kind="projections" (or rankings, rookie_rankings) writes a styled workbook to disk and returns its path. Edit the highlighted column — Proj PPG for projections, My Rank for rankings/rookies — in Excel or Google Sheets.import_excel path="…" reads it back and saves your values as overrides.get_projections, get_fantasy_rankings, and get_prospect_outcomes then automatically use your numbers (flagged in the output) until you run clear_overrides.Workbooks default to $STATHEAD_DIR (or the current working directory); pass path to choose where they land. Overrides persist in $STATHEAD_DIR/~/.stathead/overrides.json.
Run it directly — no install, no clone:
npx -y stathead-mcp
It speaks MCP over stdio, so you normally wire it into a client rather than run it by hand.
Add to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):
{
"mcpServers": { "stathead": { "command": "npx", "args": ["-y", "stathead-mcp"] } } }
claude mcp add stathead -- npx -y stathead-mcp
Use the same command/args (npx -y stathead-mcp) in the client's MCP config.
Prefer a URL over a local command? The same tools are hosted over MCP's Streamable HTTP transport by a Cloudflare Worker (workers/stathead-mcp/, deployed via deploy-workers.yml):
https://stathead-mcp.dachhack.workers.dev
Add it under Settings → Connectors → Add custom connector, paste the URL, and save — no command, no API key. (A GET to that URL returns a small health payload; clients POST JSON-RPC to it.) The npm/stdio package above stays the path for Claude Code and Cursor.
The Worker records a privacy-respecting usage counter (MCP method + tool name only — no IPs or request bodies) to a Cloudflare Analytics Engine dataset (stathead_mcp_usage). View aggregates at GET /stats once you set the CF_ACCOUNT_ID + CF_ANALYTICS_TOKEN worker secrets (wrangler secret put …), or query the dataset in the Cloudflare dashboard. npm download counts don't see remote-connector usage — this does.
Most tools fetch live from open upstreams (nflverse, Sleeper, FantasyFootballCalculator, ESPN's public endpoints). A handful read committed daily snapshots (StatHead's blended dynasty values, ADP history, in-house season projections), which the server fetches from the hosted StatHead site by default.
Please review [`DATA_SOURCES.md`](../DATA_SOURCES.md) before redistributing any data this server returns — several upstreams are proprietary or paid and carry their own terms.
All optional, via environment variables:
| Var | Default | Purpose |
|---|---|---|
STATHEAD_DATA_BASE | GitHub raw (data branch) | Base URL for committed snapshot data ( data/ ). Defaults to GitHub raw, which serves every file uncompressed/reliably (the Cloudflare host gzips files over its 25 MiB cap, which Node can't decode). Override to point at your own deployment or a local http://localhost:5173/ dev server. |
VITE_KTC_PROXY | project worker | CORS proxy for KeepTradeCut. Deploy your own (workers/ktc-proxy) to avoid shared rate limits. |
VITE_FC_PROXY | project worker | CORS proxy for FantasyCalc (workers/fc-proxy). |
VITE_ODDS_API_KEY | — | Enables betting-odds tools (the-odds-api.com). |
Running from a full repo checkout instead? The server reads snapshots straight from local public/data/ and ignores STATHEAD_DATA_BASE.
The bundle is produced from the StatHead monorepo:
# from the repo root
npm install npm run build:mcp # → mcp/dist/server.mjs (esbuild, single file) node mcp/dist/server.mjs
Bump version in mcp/package.json and SERVER_VERSION in mcp/dist/server.mjs (they must match), merge to the default branch, then any one of:
git push -f origin <commit>:publish-mcp-now # branch-push trigger (works from Claude Code sessions)
git tag mcp-v1.2.3 && git push origin mcp-v1.2.3 # tag trigger
publish-mcp.yml refuses a version already on npm and a commit not yet on the default branch, smoke-tests the bundle, publishes via npm Trusted Publishing, then chains the MCP Registry publish. Manual fallback:
npm run build:mcp # repo root — refresh the bundle
cd mcp && npm publish --access public
The published tarball is just dist/server.mjs + this README (~220 KB).
server.json is the manifest for the official MCP Registry (io.github.dachhack/stathead-mcp). After an npm publish, the Publish to MCP Registry workflow (.github/workflows/publish-mcp-registry.yml) pushes it — authenticating via GitHub OIDC for the io.github.dachhack/* namespace (no secret). The npm package carries a matching mcpName field so the registry can verify the package belongs to this entry, and the workflow syncs server.json's version from package.json so they never drift.
Most community directories (Glama, mcp.so, PulseMCP) mirror the official registry and/or auto-index public npm packages with the model-context-protocol keyword (which package.json has), so a registry publish propagates to them.
MIT — see ../LICENSE. The code is MIT; the data it returns is not necessarily redistributable. See DATA_SOURCES.md.