MCP YouTube Transcript
An MCP server retrieving transcripts of YouTube videos
Descripción del creador (original en inglés)
Local sports math, DFS settlement, bet analytics, and game-entertainment tools.
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": {
"dfs-engine": {
"command": "npx",
"args": [
"-y",
"@buzzr/mcp"
]
}
}
}Ejecuta esto en tu terminal
claude mcp add dfs-engine -- npx -y @buzzr/mcpPégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"dfs-engine": {
"command": "npx",
"args": [
"-y",
"@buzzr/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": {
"dfs-engine": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@buzzr/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 Buzzr-app, 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 (5.1.0) llegó al registro hace 4 meses.
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.
MCP server exposing the @buzzr sports engines to AI agents — DFS settlement, odds math, and entertainment predictions as tools.
@buzzr/mcp is a Model Context Protocol stdio server that puts the whole @buzzr engine family in front of any MCP-capable agent (Claude Desktop, Claude Code, or your own client). All math and policy logic lives in the underlying engines — this package is a thin, schema-validated tool surface:
@buzzr/dfs-engine — pick-em settlement with versioned compatibility and custom policies@buzzr/bets-core — no-vig fair lines, parlay pricing, expected value, Kelly staking@buzzr/entertainment-engine — ML buzz-score predictions and personalized game rankingRun it directly with npx (Node 22+). Pin the version you reviewed instead of silently accepting a future latest release:
npx -y @buzzr/mcp@5.1.0
The server speaks MCP over stdio: JSON-RPC on stdin/stdout, logs on stderr. It exposes 11 tools with bounded inputs and outputs, and does not fetch live odds, box scores, operator accounts, or private user data.
The Buzzr Sports Engine listing on Smithery packages the exact published @buzzr/mcp@5.1.0 artifact as a local stdio MCPB. It is a distribution and installation surface, not a hosted HTTP service. To add it to Codex through Smithery:
npx -y smithery@1.2.0 mcp add sarveshsea/buzzr-sports-engine --client codex
Smithery writes the corresponding MCP configuration for the selected client. Use the direct npm command above when you need both the server package and its launcher configuration pinned explicitly.
Add this to claude_desktop_config.json from Settings → Developer → Edit Config, then fully quit and reopen Claude Desktop:
{
"mcpServers": { "buzzr": { "command": "npx", "args": ["-y", "@buzzr/mcp@5.1.0"] } } }
claude mcp add --transport stdio buzzr -- npx -y @buzzr/mcp@5.1.0
For a version-controlled project configuration, add this to .mcp.json, trust the project when prompted, and start a new Claude Code session:
{
"mcpServers": { "buzzr": { "command": "npx", "args": ["-y", "@buzzr/mcp@5.1.0"] } } }
Confirm it with claude mcp get buzzr; inside Claude Code, /mcp shows the connection and discovered tool count.
Add this to the repository's .cursor/mcp.json (or the equivalent user-level MCP configuration), then fully restart Cursor:
{
"mcpServers": { "buzzr": { "command": "npx", "args": ["-y", "@buzzr/mcp@5.1.0"] } } }
Open Cursor Settings → MCP to confirm buzzr connected and exposed 11 tools. See Cursor's MCP documentation if your installed Cursor version presents a different settings location.
The Codex CLI, IDE extension, and app share config.toml. The one-command user setup is:
codex mcp add buzzr -- npx -y @buzzr/mcp@5.1.0
Or add the equivalent block to ~/.codex/config.toml for all projects, or to a trusted repository's .codex/config.toml for that project only:
[mcp_servers.buzzr]
command = "npx" args = ["-y", "@buzzr/mcp@5.1.0"]
Run codex mcp get buzzr, then start a new Codex task after changing the configuration.
Use this process configuration in any client that accepts a command plus args:
{
"name": "buzzr", "transport": "stdio", "command": "npx", "args": ["-y", "@buzzr/mcp@5.1.0"], "env": {} }
Treat stdout as JSON-RPC only, read diagnostics from stderr, and close the child process's stdin during shutdown. The client must perform the MCP lifecycle below; starting npx in a terminal and seeing it remain open is normal for a stdio server waiting for a client.
The client sends initialize first. Verify the serverInfo.name field is "buzzr", the serverInfo.version field is the installed package version, and the response has a capabilities.tools object. Send notifications/initialized, then call tools/list. The server returns the 11 tools in the catalog below with their input schemas. It does not advertise data fetching, resources, or prompts.
examples/mcp-calls.json is a machine-readable JSON-RPC transcript with the initialization expectation, exact tool discovery order, and a safe list_book_policies → validate_dfs_entry → grade_dfs_entry workflow. The repository replays that workflow through a real MCP client in CI.
node --version, npm --version, and npx --version.npm view @buzzr/mcp@5.1.0 version, then run npm cache verify. If npm reports cache corruption, repair npm's cache before retrying; npm cache clean --force is a last resort because it removes the whole local cache.PATH than an interactive shell. On macOS or Linux, run command -v npx; on Windows, run where.exe npx. If the client cannot find npx, use that absolute path as command (normally npx.cmd on Windows) or launch the client from an environment where Node is on PATH.listening on stdio diagnostic to stderr and waits for JSON-RPC input.| Tool | Engine | What it does |
|---|---|---|
grade_dfs_entry | @buzzr/dfs-engine | Settle one transport-bounded 1–12-leg entry; executable built-in policies currently allow at most 6 PrizePicks or 8 Underdog legs. |
grade_dfs_entries | @buzzr/dfs-engine | Settle 1–50 entries, up to 600 total legs, with bounded concurrency and isolated failures. |
validate_dfs_entry | @buzzr/dfs-engine | Return structured engine validation issues for a candidate entry without settling it. |
list_book_policies | @buzzr/dfs-engine | List authoritative executable profile snapshots and metadata-only drafts, including status, verification, sources, and complete play types. |
fair_line | @buzzr/bets-core | Remove vig from both sides of one two-way market. |
closing_line_value | @buzzr/bets-core | Compare placed and closing prices for the same selection. |
parlay_value | @buzzr/bets-core | Price independent parlay legs, compare offered odds, and optionally calculate expected value. |
kelly_stake | @buzzr/bets-core | Calculate full and fractional Kelly stakes from a supplied win probability. |
summarize_bet_history | @buzzr/bets-core | Summarize up to 500 bets with overall and UTC-period rollups, drawdown, and streaks. |
predict_game_buzz | @buzzr/entertainment-engine | Predict one game's 1–10 entertainment score with confidence and factor detail. |
rank_games | @buzzr/entertainment-engine | Rank 1–100 candidate games for a bounded taste profile. |
Tool strings, identifiers, arrays, stdio frames, concurrent calls, and serialized results are bounded. American odds must be within [-100000, -100] or [100, 100000]. grade_dfs_entries, closing_line_value, and summarize_bet_history return string contractVersion: "1".
Operator-named policies are independent compatibility profiles, not official rules engines or evidence of affiliation:
Displayed lineup terms are authoritative. Call list_book_policies before grading, inspect verification and sources, and obtain explicit operator rulings for DNPs, reboots, ties, rescues, voids, and corrections. The tool lists future fixtures with executable: false; grading tools reject draft book IDs because drafts are metadata, not settlement implementations.
invalid_input result through an MCP client transport or a direct exported tool.handler(...) call. At most eight compact validation issues are included; raw Zod errors are never returned.tools/call request with invalid tool arguments.validate_dfs_entry intentionally accepts a bounded candidate object and returns the engine's structured validation report.isError: true results such as tool_execution_failed, entry_settlement_failed, server_busy, or result_too_large. Internal error details are not public."Did my PrizePicks slip hit?"
User: I had a $10 2-pick power play: LeBron over 25.5 points (he scored 31)
and Curry over 27.5 (he scored 33). What's the payout?
Agent calls
grade_dfs_entry:
`json
{
"entryId": "slip-1",
"bookId": "prizepicks",
"playTypeId": "power",
"stake": 10,
"displayedMultiplier": 3,
"legs": [
{ "legId": "l1", "playerName": "LeBron James", "league": "NBA", "propType": "points", "line": 25.5, "direction": "over", "actual": 31 },
{ "legId": "l2", "playerName": "Stephen Curry", "league": "NBA", "propType": "points", "line": 27.5, "direction": "over", "actual": 33 }
]
}
`
Result:
"status": "won","payout": { "total": 30, "withdrawable": 30, "bonus": 0 }—
both supplied actuals clear their lines and the submitted 3× displayed multiplier
is consistent with the selected compatibility table. Confirm the actual entry
details before tr
Solo se muestra el principio; lee el resto en el repo