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Sportiq Mcp

ninjabeam20/sportiq-mcp
6STDIOregistry active
Summary

Three sports, three flagship tools: Monte Carlo bracket simulation for the 48-team World Cup 2026 format using Poisson xG, F1 pit strategy prediction with tyre degradation models over OpenF1 telemetry, and a PuLP constraint solver that builds valid Dream11 cricket lineups under salary and role caps. Beyond the headliners you get 44 raw and intelligence tools pulling from API-Football, Jolpica, CricAPI, and live bookmaker odds. The server includes value bet finders that compare model probabilities against market lines. A hosted instance runs on Cloud Run if you want to skip local setup. Useful when you need structured sports intelligence beyond static lookups.

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sportiq-mcp

CI PyPI Python License: MIT MCP Registry

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 demo — Claude calling football_simulate_bracket for World Cup 2026 title probabilities

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)

Sponsor SportIQ   Website

Sponsor at $10/mo and you get a SportIQ Pro key that unlocks all the paid intelligence tools (the three flagships + everything in the INTEL columns below). One-time $49 lifetime for the first 50 backers.

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)

SportRAW (free)INTEL (Pro)
Football (WC 2026)groups, fixtures, standings, squad, match stats, top scorers, oddsxg_model, match_predictor, simulate_group, simulate_bracket, knockout_path, form_trends, find_value_bets, build_accumulator
F1sessions, drivers, lap_times, standings, race_results, weathertyre_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_oddsbuild_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.

Free tools work out of the box — standings, schedules, squads, fixtures, plus the WC 2026 bracket simulation (football_simulate_bracket) as a free showcase. To unlock the rest of the Pro intelligence tools here, paste the personal …/u/<your-key>/mcp connector link from your sponsorship welcome email instead of the plain URL.

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": {
        "SPORTIQ_PRO_KEY": "sq_your_pro_key",
        "CRICAPI_KEY": "your_cricapi_key",
        "APIFOOTBALL_KEY": "your_apifootball_key",
        "THEODDS_KEY": "your_theodds_key"
      }
    }
  }
}

All env vars are optional — the server boots and serves seed/free-source data with no keys. Add SPORTIQ_PRO_KEY (from a sponsorship) to unlock the intelligence tools, or a data-source key to unlock the source it gates.

VarUnlocksFree tier
SPORTIQ_PRO_KEYThe 24 Pro intelligence tools — sponsor to get a key—
APIFOOTBALL_KEYLive football fixtures / standings / squads / scorers100 req/day
THEODDS_KEYMarket odds (football + cricket probability tools)500 req/month
FOOTBALLDATA_KEYfootball-data.org fallback (token optional)10 req/min
CRICAPI_KEYLive cricket scores / scorecards / schedules / squads100 req/day
RAPIDAPI_KEYPaid Cricbuzz fallback (player career stats)plan-dependent
SPORTIQ_ENABLE_NDTV / SPORTIQ_ENABLE_CRICBUZZOpt-in cricket scrapers (off by default — ToS)—
REDIS_URLShared cache backend (defaults to local diskcache)—
SPORTIQ_TRANSPORTstdio (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.

SportIQ Pro

Raw-data tools and sportiq_health are free and need no key. The intelligence tools (everything in the INTEL columns, including the three flagships) require a SportIQ Pro key.

Sponsor at github.com/sponsors/Ninjabeam20 — $10/mo (or one-time $49 lifetime, first 50 backers) — and your welcome email delivers your Pro key. It contains two things:

  • a Pro key → for local installs, set it as the SPORTIQ_PRO_KEY env var;
  • a personal connector link → for claude.ai / ChatGPT, add it as a custom connector with No authentication (the key rides inside the link).

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.md for 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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Registryactive
Packagesportiq-mcp
TransportSTDIO
UpdatedJun 8, 2026
View on GitHub