MCP server for FIFA World Cup 2026 football, Formula 1, and IPL cricket intelligence tools.
Project description
sportiq-mcp
MCP server that turns any AI assistant into a sports analyst across FIFA World Cup 2026 football, Formula 1, and IPL cricket — 44 AI-callable tools.
SportIQ running live in Claude — Monte Carlo World Cup bracket, F1 pit strategy, and Dream11 optimisation, each a visible MCP tool call. (1-min demo)
Every tool is free — the three flagships and everything in the INTEL columns below, no key, no account. If SportIQ is useful to you, sponsor the project to support ongoing development. It's a donation, not a paywall — nothing is locked behind it.
What it does
Raw-data tools are table stakes; the intelligence layer is the product. Three flagships:
football_simulate_bracket— Monte Carlo with Poisson xG over the 48-team WC 2026 format → per-team round + title probabilities.f1_predict_pit_strategy— tyre-degradation model on OpenF1 telemetry → optimal stop laps + compound sequence.cricket_build_dream11_team— PuLP constraint solver → a valid fantasy XI under credit/role/team caps.
Tools (44 total)
| Sport | RAW data | INTEL |
|---|---|---|
| Football (WC 2026) | groups, fixtures, standings, squad, match stats, top scorers, odds | xg_model, match_predictor, simulate_group, simulate_bracket, knockout_path, form_trends, find_value_bets, build_accumulator |
| F1 | sessions, drivers, lap_times, standings, race_results, weather | tyre_degradation, undercut_window, head_to_head_pace, weather_strategy_impact, qualifying_analysis, race_pace_compare, predict_pit_strategy |
| Cricket (IPL) | live_matches, scorecard, points_table, schedule, squad, live_odds | build_dream11_team, captain_recommendation, differential_picks, player_form_index, pitch_report, head_to_head, player_matchup, find_value_bets |
| Cross-sport | — | build_accumulator |
Plus sportiq_health (cache backend + per-adapter status and remaining API quota).
Data sources (per chain, with keyless fallbacks): football → API-Football → football-data.org → bundled wc2026.json. F1 → OpenF1 → Jolpica → fastf1. Cricket → CricAPI + static seeds (NDTV/Cricbuzz scrapers opt-in).
Where it works
Anywhere that speaks MCP — Claude (Desktop + web), ChatGPT, Cursor, and any MCP client. Two ways to run it:
- Hosted (no install): add a custom connector — works in claude.ai web & ChatGPT.
- Local (
uvx/Desktop config/IDEs): install from PyPI.
How it works
Hosted — no install
A public instance runs on Google Cloud Run. Add this as a custom connector with No authentication:
https://sportiq-mcp-329580761892.us-central1.run.app/mcp
- claude.ai (web): Settings → Connectors → Add custom connector → paste URL → Save.
- ChatGPT: Settings → Apps & Connectors → enable Developer mode → Create app (MCP) → paste URL → No authentication → Connect.
All 44 tools work out of the box on the plain URL above — data tools and the full intelligence layer (bracket simulation, pit strategy, Dream11, value bets). No key, no account, nothing to unlock.
First request after idle takes ~5–10s (the server scales to zero, so it wakes up); fast after that.
Local install
uvx sportiq-mcp # from PyPI
# or from source:
git clone https://github.com/Ninjabeam20/SportIQ-MCP && cd sportiq-mcp
uv sync && uv run python -m sportiq.server
Claude Desktop config:
{
"mcpServers": {
"sportiq": {
"command": "uvx",
"args": ["sportiq-mcp"],
"env": {
"CRICAPI_KEY": "your_cricapi_key",
"APIFOOTBALL_KEY": "your_apifootball_key",
"THEODDS_KEY": "your_theodds_key"
}
}
}
}
Every tool works with no keys — the server boots and serves seed/free-source data, and the whole intelligence layer runs locally. Data-source keys are optional and only upgrade the source a tool reads from (fresher/live data); they never unlock tools.
| Var | Unlocks | Free tier |
|---|---|---|
APIFOOTBALL_KEY |
Live football fixtures / standings / squads / scorers | 100 req/day |
THEODDS_KEY |
Market odds (football + cricket probability tools) | 500 req/month |
FOOTBALLDATA_KEY |
football-data.org fallback (token optional) | 10 req/min |
CRICAPI_KEY |
Live cricket scores / scorecards / schedules / squads | 100 req/day |
RAPIDAPI_KEY |
Paid Cricbuzz fallback (player career stats) | plan-dependent |
SPORTIQ_ENABLE_NDTV / SPORTIQ_ENABLE_CRICBUZZ |
Opt-in cricket scrapers (off by default — ToS) | — |
REDIS_URL |
Shared cache backend (defaults to local diskcache) | — |
SPORTIQ_TRANSPORT |
stdio (default, local) or http (remote/Cloud Run) |
— |
macOS arm64: the Dream11 solver needs CBC —
brew install cbc(the binary bundled with PuLP is x86-only).
Self-host
Set SPORTIQ_TRANSPORT=http and the server serves the MCP endpoint at /mcp (binds 0.0.0.0:$PORT). A ready-to-build Dockerfile is included; see cloud.md for a Google Cloud Run deploy (free tier). With your own keys set, the live-score and odds tools come online too.
Support SportIQ
Every tool is free and open source — the raw-data tools, sportiq_health, and the full intelligence layer (the three flagships + everything in the INTEL columns). No key, no account, nothing gated.
If SportIQ saves you time, sponsor the project at github.com/sponsors/Ninjabeam20 to help fund hosting and ongoing development. It's a voluntary donation — you get the same fully-unlocked server either way.
Is it safe?
- Open source, MIT licensed, published on PyPI with signed build attestations — read the code before you connect it.
- Read-only. Tools only fetch and analyse public sports data — no write, delete, payment, email, or file-system tools.
- No data collection. It answers a tool call and forgets it.
- The hosted instance holds no secrets — it runs with zero API keys.
- Independently reviewed by AI code-audit agents (verdict: ship-ready, clean) — see
SECURITY.mdfor the full trust model.
Every response carries a meta.is_stale flag + data age, so the AI tells you how fresh each answer is. Live scores refresh ~30s, F1 telemetry ~10s, standings ~10min, fixtures ~6h.
Develop
uv sync --extra dev
uv run pytest
uv run ruff check .
npx @modelcontextprotocol/inspector uv run python -m sportiq.server
See CLAUDE.md for collaboration rules and docs/index.md for the wiki entry point.
Data sources & credits
SportIQ derives some model constants offline from open datasets. Raw datasets are never shipped or fetched at runtime — only small derived seeds (circuits.json, venues.json, elo_seed.json) are committed.
- F1DB (CC BY 4.0) — per-circuit stop counts + lap lengths; pit loss measured offline from OpenF1 laps.
- Cricsheet — ball-by-ball IPL data → derived venue scoring priors (
venues.json). - martj42 international football results (CC0) — Elo backtesting.
- OpenF1 — keyless live F1 telemetry (runtime source).
- football-data.org — free football data (runtime source).
License & author
Created and maintained by Utkarsh Gupta (@Ninjabeam20). Licensed under the MIT License — © 2026 Utkarsh Gupta. Canonical package: sportiq-mcp on PyPI / io.github.Ninjabeam20/sportiq-mcp in the official MCP registry.
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