Collegefootballdata Mcp

io.github.mrfentmen由 GitHub 帳號 mrfentmen 發布v1.0.0更新於 Nov 6, 2026

College football: conferences, venues, teams, games, scoreboards, team stats and lines.

已驗證STDIO僅桌面金融資料與分析

概覽

AI 產生的概覽

為助理提供大學美式足球參考資料:聯盟、場館、球隊、賽事、即時比分、統計、排名與盤口。

可以做什麼
  • 查詢聯盟、場館與球隊,包含名稱、隊色、吉祥物、所屬聯盟與分區
  • 取得賽季或單週賽程、比分、開賽時間,以及即時比分板
  • 讀取球隊與球員的技術統計、賽季總計、進階效率數據及 SP+/SRS 評分
  • 查看投票排名、招募球員與球隊招募排名,以及教練與其執教經歷
  • 查看讓分、大小分與勝負盤口,以及賽事天氣預報
  • 依姓名片段搜尋球員,並了解哪些週為例行賽、哪些為季後賽
適用情境
適合讓助理直接回答大學美式足球相關問題,例如賽程、賽果、統計、排名、招募或盤口,不必手動查資料。適合球迷、撰稿人與分析師以單一賽季或單週為單位使用。
執行需求
以本機 stdio 程序執行,需從 npm 套件 collegefootballdata-mcp 安裝,因此需要 Node.js 與 npm。未宣告任何驗證、環境變數或請求標頭;README 表示多數伺服器讀取公開資料,無需自備金鑰。
安裝前請注意
資料來自上游大學美式足球資料來源,準確性與時效取決於該來源,即時比分板的新鮮度亦然。盤口資訊僅供參考,可能已過期。README 提到同一儲存庫中部分套件仍帶有只回覆「尚未實作」的工具,安裝前應確認所需工具確實可用。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Collegefootballdata Mcp,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

awesome-servers

One repo for three families of servers, each subtree keeping its own layout and tooling so it can still be built, run and published on its own.

SubtreeWhat it holdsRun one
mcp/338 TypeScript MCP servers, plus 1107 published packages in published/cd mcp/servers/<slug> && npm install && npm run build
acp/79 Python ACP agentspython3 acp/agents/<name>/agent.py
a2a/37 Python A2A servers plus the shared a2a_kitpython3 a2a/servers/<name>/server.py
watchd/a threshold watcher that runs the feeds between editor sessionspython3 watchd/watchd.py --config conditions.json --loop
site/the published site: registry with search, the public-feed atlas, watchd planshttps://mrfentmen.github.io/awesome-servers/

Most servers read public data with no key of their own; the ones wrapping a vendor API take that vendor's key. Nothing in this repo asks a caller to pay. On 2026-10-17 the licence machinery was removed for good: the per-tool src/license.ts gates are gone from the MCP servers, and the A2A and ACP trees no longer carry the hosted licence-gateway half — the skills that used it now answer with an explicit not-implemented stub. Nothing here asks a caller to pay, and nothing they run is refused with a buy link.

Nothing here is generated: each subtree's README says what its servers read, and every server has its own unit tests (mcp/servers/<slug>/tests, acp/agents/<name>/tests, a2a/servers/<name>/tests) plus a live smoke check (tools/smoke*.py, a2a/tools/smoke_all.py).

Novel and original

Nearly all of this is first-of-its-kind work, not a port of an existing catalogue. Before each server or agent was built, it was checked against the official tool lists (the MCP registries, agentclientprotocol.com's agent list and registry) and a live GitHub search for the same domain, and the research logs record what was found and why it still counted as missing — see mcp/MISSING.md, acp/MISSING.md and a2a/docs/. Highlights:

  • The MCP side holds TypeScript servers, one npm package each, and 1039 published packages under published/; mcp/MISSING.md documents the check that preceded every build: what was searched, what was skipped and why the domain still counted as uncovered.
  • On the ACP side there were zero domain agents before this repo — every agent on the official list was a coding agent. These 79 Python agents are the first non-coding ACP agents, and several use protocol surfaces no other agent uses in production (session/request_permission for dataset reads, fs/write_text_file for a briefing file, session/cancel for a conditional watch, image content blocks, a live SSE push feed), each proved-unused in the wild by search at build time. Two more firsts carry their own proof: the orchestrator is an agent whose feeds are agents — it spawns sibling repo agents as real ACP child processes and merges their answers — and the nyc pack is the first multi-agency city surface.
  • acp/MISSING.md doubles as the public-feed atlas: every keyless feed probed live, with its date, what it answered and whether it still works. The published site renders that table at https://mrfentmen.github.io/awesome-servers/atlas.html.
  • The pattern across all three subtrees is the same thesis: wrap one real, keyless public dataset, answer honestly about what the feed did and did not say, and keep the whole thing small, tested and self-contained.

Publishing

  • MCP servers publish from mcp/servers/<slug> (its own package.json, version and README).
  • ACP and A2A servers are repo-run today (Python, no packaging step).

Built on top of it

Creatures that use this corpus as their world live in the sibling repo mrfentmen/superagents (public, with its own claim-check in MISSING.md):

  • polymath — routes your question to the most fitting agents of this repo, spawns each as a real ACP child process, and merges the answers into one brief with per-row citations; a sibling that fails appears as a named row, never silence. Its registry is a data file and its ranking is deterministic word-scoring, not a model opinion.
  • sentry — one plain sentence ("watch air quality in Denver over 150") becomes a tracked watch: a permission-asked protocol write produces the conditions file this repo's watchd/ obeys unchanged, plus the activation lines. Checks it can author today: air thresholds, quake magnitudes within a radius, river gauges at flood stage.
  • fedora hat guy — the persona agent in his own repo mrfentmen/fedora-hat: says "never miss" and means it — one sentence installs the full crown of watches (air + quakes, gauge-named flood) in one permissioned write, and your other questions are forwarded to the siblings above with every row cited.
  • instink — the instinct agent in his own repo mrfentmen/instink: compiles a skill into a reflex — a matcher plus the answer it fires, with hit/miss counters and honest promotion/demotion. The skill doc stays one step away, never deleted.
  • contextink — the context agent in his own repo mrfentmen/contextink: you say "do this" and it acquires the context from the repo, git, and recent files so you don't have to explain it; asks only the minimal high-information-gain questions when acquisition fails.
  • rewind — the replay agent in his own repo mrfentmen/rewind: replays agent runs and mutates one variable to see what would have happened. Replay + mutate + diff for agent traces.
  • scopink — the scope agent in his own repo mrfentmen/scopink: checks if an action is within the scope of what was asked. Detects scope creep in agent plans.
  • curious — the curiosity agent in his own repo mrfentmen/curious: proactively seeks information it doesn't have. Scans for knowledge gaps, seeks answers, learns facts.
  • bored — the idle agent in his own repo mrfentmen/bored: uses idle time productively. Consolidates memories, explores areas, prepares for tasks.

Point the polymath at a checkout of this repo with AWESOME_SERVERS_HOME=$PWD/awesome-servers and it federates across the two repos live.

Published snapshot (published/)

published/ holds one directory per npm package, byte-for-byte what the registry serves: 1039 packages, every version matching npm latest.

  • published/INDEX.md is generated from the tree by python3 scripts/index-published.py.
  • scripts/sync-published-snapshot.py re-downloads every package from npm; run it only when every local fix has been published, because it overwrites dist/ from the tarballs.
  • One package carries a licence gate (MCP_LICENSE_KEY): @mrfentmen/vg-resource-mcp. Another 495 still ship tools that answer Not yet implemented; published/INDEX.md lists every one of them.
  • Every package links to this repo (mrfentmen/awesome-servers) as its source.

servers/ holds the older per-server source that predates the snapshot. Where the two disagree, published/ is what users actually install.

來源:README.md,提交 ee04f93

工具

20

cfbd_conferences

List every FBS/FCS conference with its full name and abbreviation.

無需輸入參數。

cfbd_venues

List college football venues with capacity, city, state, elevation and surface.

無需輸入參數。

cfbd_teams

List teams with colors, logos, mascot, conference and division.

輸入參數conference

cfbd_games

Games for a season/week with scores, venue and start time. Returns compact rows.

輸入參數teamweekyearconferenceseasonType

cfbd_scoreboard

Live scoreboard for a week (useful for games in progress; no year needed means the current slate).

輸入參數teamweekyearconferenceseasonType

cfbd_game_team_stats

Per-team box score stats for games in a season/week (total yards, turnovers, ...).

輸入參數teamweekyearconferenceseasonType

cfbd_betting_lines

Betting lines for games: spread, over/under and moneylines from several books.

輸入參數teamweekyearconferenceseasonType

cfbd_game_weather

Forecasted weather for games in a season/week.

輸入參數teamweekyearconferenceseasonType

cfbd_rankings

Polls for a season/week (AP Top 25, Coaches, CFP Rankings, ...). Optional poll filter and top_n slice.

輸入參數pollweekyeartop_nseasonType

cfbd_player_game_stats

Per-player game statistics for a season/week, optionally per team or conference.

輸入參數teamweekyearconferenceseasonType

cfbd_team_season_stats

Full team season totals by stat category for a year, optionally one team or conference.

輸入參數teamyearconferenceseasonType

cfbd_advanced_game_stats

Advanced (per-game) team efficiency stats for a season/week, optionally per team.

輸入參數teamweekyearconferenceseasonType

cfbd_player_season_stats

Player season stats filtered by category (passing, rushing, receiving, defensive, ...).

輸入參數teamyearconferenceseasonType

cfbd_recruiting_players

Recruited players for a year with stars, position, ranking, rating and committed school.

輸入參數teamyearconference

cfbd_recruiting_teams

Team recruiting rankings for a year: points, average rating, commits.

輸入參數teamyearconference

cfbd_coaches

Coaches with their full career stints; filter by team or name fragment.

輸入參數teamyearlastNamefirstName

cfbd_sp_plus_ratings

Bill Connelly SP+ team ratings for a year (offense/defense/special teams).

輸入參數teamyearconference

cfbd_srs_ratings

Simple Rating System (SRS) team ratings for a year.

輸入參數teamyearconference

cfbd_season_calendar

The season calendar: which weeks carry regular vs postseason games.

輸入參數year

版本歷史

1
  1. v1.0.0最新Oct 29, 2026

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