MCP YouTube Transcript
An MCP server retrieving transcripts of YouTube videos
作者提供的说明(英文原文)
Local sports math, DFS settlement, bet analytics, and game-entertainment tools.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"dfs-engine": {
"command": "npx",
"args": [
"-y",
"@buzzr/mcp"
]
}
}
}在终端中运行这条命令
claude mcp add dfs-engine -- npx -y @buzzr/mcp粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"dfs-engine": {
"command": "npx",
"args": [
"-y",
"@buzzr/mcp"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"dfs-engine": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@buzzr/mcp"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
你的选择通过 Cookie 保存在这台设备上,无需账户。
这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月6日
注册名称已通过 GitHub 账户 Buzzr-app 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于–,最新版本(5.1.0)于4个月前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。
同一分类中有:MCP YouTube Transcript, Google Analytics MCP, BibiGPT YouTube Video Summarizer
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
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.
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
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
只显示了开头部分;其余内容请在仓库中阅读