Collegefootballdata Mcp

io.github.mrfentmen由 GitHub 账号 mrfentmen 发布v1.0.0更新于 Nov 6, 2026

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

已验证STDIO仅桌面金融数据与分析

概览

AI 生成的概览

为助手提供大学橄榄球参考数据:联盟、场馆、球队、比赛、实时比分、统计、排名与盘口。

可以做什么
  • 查询联盟、场馆与球队,含名称、队色、吉祥物、所属联盟与分区
  • 获取赛季或单周赛程、比分、开赛时间,以及实时比分板
  • 读取球队与球员的技术统计、赛季总计、进阶效率数据及 SP+/SRS 评分
  • 查看投票排名、招募球员与球队招募排名,以及教练及其执教经历
  • 查看让分、大小分与胜负盘口,以及比赛天气预报
  • 按姓名片段搜索球员,并了解哪些周为常规赛、哪些为季后赛
适用场景
适合让助手直接回答大学橄榄球相关问题,例如赛程、赛果、统计、排名、招募或盘口,无需手动查资料。适合球迷、撰稿人和分析师按单个赛季或单周使用。
运行要求
以本地 stdio 进程运行,需从 npm 包 collegefootballdata-mcp 安装,因此需要 Node.js 与 npm。未声明任何认证、环境变量或请求头;README 称多数服务器读取公开数据,无需自带密钥。
安装前请注意
数据来自上游大学橄榄球数据源,准确性与时效取决于该来源,实时比分板的新鲜度同样如此。盘口信息仅供参考,可能已过期。README 提到同一仓库中部分包仍带有仅返回“尚未实现”的工具,安装前应确认所需工具确实可用。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Collegefootballdata Mcp,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。

其他 MCP 客户端

参照 仓库 中的启动说明。

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.

来源:README.md,提交 ee04f93

工具

20

cfbd_conferences

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

无需输入参数。

cfbd_venues

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

无需输入参数。

cfbd_teams

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

输入参数conference

cfbd_games

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

输入参数teamweekyearconferenceseasonType

cfbd_scoreboard

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

输入参数teamweekyearconferenceseasonType

cfbd_game_team_stats

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

输入参数teamweekyearconferenceseasonType

cfbd_betting_lines

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

输入参数teamweekyearconferenceseasonType

cfbd_game_weather

Forecasted weather for games in a season/week.

输入参数teamweekyearconferenceseasonType

cfbd_rankings

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

输入参数pollweekyeartop_nseasonType

cfbd_player_game_stats

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

输入参数teamweekyearconferenceseasonType

cfbd_team_season_stats

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

输入参数teamyearconferenceseasonType

cfbd_advanced_game_stats

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

输入参数teamweekyearconferenceseasonType

cfbd_player_season_stats

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

输入参数teamyearconferenceseasonType

cfbd_recruiting_players

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

输入参数teamyearconference

cfbd_recruiting_teams

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

输入参数teamyearconference

cfbd_coaches

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

输入参数teamyearlastNamefirstName

cfbd_sp_plus_ratings

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

输入参数teamyearconference

cfbd_srs_ratings

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

输入参数teamyearconference

cfbd_season_calendar

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

输入参数year

版本历史

1
  1. v1.0.0最新Oct 29, 2026

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