Stathead MCP
概览
作者提供的说明(英文原文)
Fantasy football analytics: stats, dynasty, projections, prospects, Sleeper leagues, Excel I/O
PopNx MCP 的三大支柱
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。
- 用户评价i暂无评价评价功能将在后续阶段与账户功能一起开放
- 我们的基础检查i1 项中通过 1 项依据公开信息检查;尚未扫描代码
- 使用情况i起步阶段↓ 384/周 · ★ –
它能帮你做什么
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。
- 连接方式: 在你的电脑上运行
- 传输方式: stdio
- 分类: 营销与社交媒体
安装
选择你使用的 AI 应用,然后复制设置。
安装之前
- 基础检查:1 项中通过 1 项
- 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
- 注册中心没有列出需要填写的密钥。
你需要
- npm已安装 Node.js(用于 npx 命令)
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": {
"stathead": {
"command": "npx",
"args": [
"-y",
"stathead-mcp"
]
}
}
}在终端中运行这条命令
claude mcp add stathead -- npx -y stathead-mcp或者自己复制设置
粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"stathead": {
"command": "npx",
"args": [
"-y",
"stathead-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。
或者自己复制设置
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"stathead": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"stathead-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。
它能做什么
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。
基础检查i
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10日
- ✓ 通过
作者与仓库一致
注册名称已通过 GitHub 账户 dachhack 验证,该账户拥有此仓库
- … 尚未检查
仍在维护
我们还没有从 GitHub 读取这个仓库
- … 尚未检查
有许可证
我们还没有从 GitHub 读取这个仓库
- – 不适用
端点有响应
它在你的电脑上运行,没有互联网端点
- – 不适用
使用 OAuth 登录
在你的电脑上运行,改用本地设置
- … 尚未检查
工具描述中没有隐藏指令
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“营销与社交媒体”中的其他服务器比较i
- 星标数多于此分类中其他 3691 个服务器的 0%
- 发布到注册中心的时间比此分类中其他 3691 个服务器的 88% 更新
- 基础检查结果等于或优于此分类中其他 3691 个服务器的 100%
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。
常见问题
Stathead MCP 安全吗?
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。
它需要哪些密钥或代码?
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。
它在我的电脑上运行还是在云端?
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)。
它还在维护吗?
GitHub 仓库最后更新于–,最新版本(1.0.126)于4天前进入注册中心。
哪些应用可以使用它?
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。
有什么可以替代它?
同一分类中有:MCP YouTube Transcript, Google Analytics MCP, BibiGPT YouTube Video Summarizer
替代选择
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:↓ 每周下载量i★ 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
Google Analytics MCP
GA4 MCP server for AI agents: schema discovery, server-side aggregation, analysis-ready defaults.
BibiGPT YouTube Video Summarizer
AI video summarizer: summarize and transcribe YouTube, Bilibili, TikTok and podcast videos.
作者的 README
打开 README
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。
stathead-mcp
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.
What you get
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 |
Bring your own projections & rankings
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"(orrankings,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, andget_prospect_outcomesthen automatically use your numbers (flagged in the output) until you runclear_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.
Quick start
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.
Claude Desktop
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 Code
claude mcp add stathead -- npx -y stathead-mcp
Cursor / other MCP clients
Use the same command/args (npx -y stathead-mcp) in the client's MCP config.
Claude mobile apps / claude.ai web / Claude Desktop (remote connector)
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.
Data sources & freshness
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.
Configuration
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.
Building from source
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
Publishing
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
or Actions → "Publish stathead-mcp to npm" → Run workflow
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).
Listing in the MCP Registry
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.
License
MIT — see ../LICENSE. The code is MIT; the data it returns is not necessarily redistributable. See DATA_SOURCES.md.