# sportiq-mcp **Category:** 💻 Developer Tools **Repository:** https://github.com/Ninjabeam20/SportIQ-MCP **Views:** 0 **Installs:** 0 **Upvotes:** 0 **Directory Page:** https://allmcps.com/mcp/sportiq-mcp ## Description MCP tools for FIFA World Cup 2026 football, Formula 1, and IPL cricket — sims, strategy, fantasy. ## Claude Desktop Quick Installation Heuristic fallback — verify the package name and runner against the repository README before running it. Uses `npx` (confidence: low): ```json "mcpServers": { "sportiq-mcp": { "command": "npx", "args": ["-y","sportiq-mcp"] } } ``` ## Documentation & README # sportiq-mcp [![CI](https://github.com/Ninjabeam20/SportIQ-MCP/actions/workflows/test.yml/badge.svg)](https://github.com/Ninjabeam20/SportIQ-MCP/actions/workflows/test.yml) [![PyPI](https://img.shields.io/pypi/v/sportiq-mcp.svg)](https://pypi.org/project/sportiq-mcp/) [![Python](https://img.shields.io/pypi/pyversions/sportiq-mcp.svg)](https://pypi.org/project/sportiq-mcp/) [![License: MIT](https://img.shields.io/badge/License-MIT-green.svg)](LICENSE) [![MCP Registry](https://img.shields.io/badge/MCP%20Registry-listed-blue)](https://registry.modelcontextprotocol.io) 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](docs/assets/demo.gif) *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](docs/assets/SportIQ.mp4))*

Sponsor SportIQ   Website

> **Every tool is free to use** — the three flagships and everything in the INTEL columns below have no SportIQ paywall or account requirement. Live/provider-backed data still depends on the keys and quota available to the host or local operator. If SportIQ is useful to you, [sponsor the project](https://github.com/sponsors/Ninjabeam20) to support ongoing development. ## 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](https://www.api-football.com) → [football-data.org](https://football-data.org) → bundled `wc2026.json`. F1 → [OpenF1](https://openf1.org) → [Jolpica](https://jolpi.ca) → `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 register on the plain URL. Whether a live/provider-backed call can return current data depends on the credentials, quota, and fallbacks available to the hosted operator; the repository does not claim the public instance's current key inventory. | Mode | What is available | |------|-------------------| | **Hosted** | All tools register; live/provider-backed results depend on the host's current keys, quota, and fallbacks. | | **Local, keyless** | All tools register; bundled seeds and keyless sources work where supported, while credential-only live sources are skipped. | | **Local, BYO keys** | The same tools can use the configured providers for fresher/live data, subject to provider quota. | The hosted HTTP boundary rejects request bodies over 1 MiB, limits traffic to 60 requests per client and 300 total requests per minute, and permits at most two concurrent expensive model/solver calls. These counters are per process, so the documented Cloud Run configuration requires one maximum instance. > First request after idle takes ~5–10s (the server scales to zero, so it wakes up); fast after that. ### Local install ```bash uvx sportiq-mcp # from PyPI # or from source: git clone https://github.com/Ninjabeam20/SportIQ-MCP && cd sportiq-mcp uv sync --extra dev --extra analytics && uv run python -m sportiq.server ``` **Claude Desktop config:** ```json { "mcpServers": { "sportiq": { "command": "uvx", "args": ["sportiq-mcp"], "env": { "CRICAPI_KEY": "your_cricapi_key", "APIFOOTBALL_KEY": "your_apifootball_key", "THEODDS_KEY": "your_theodds_key" } } } } ``` The server boots and registers every tool without keys. Seed/keyless fallbacks and the intelligence layer work where their required inputs are available; provider keys add fresher/live sources and quota rather than unlocking a separate paid tool tier. | 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`](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). SportIQ has no paid feature gate; provider-backed data can still require operator credentials and quota. If SportIQ saves you time, **[sponsor the project at github.com/sponsors/Ninjabeam20](https://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](https://pypi.org/project/sportiq-mcp/) 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. - **Limited operational telemetry.** HTTP mode logs client software name/version, User-Agent, tool name, outcome, latency, selected source, and staleness; Cloud Run may also retain platform network/request metadata. Local stdio emits local logs but sends no SportIQ-host telemetry. - **Hosted abuse controls.** HTTP POST bodies are capped at 1 MiB; requests are limited to 60/client/minute and 300/process/minute; the five expensive simulation/strategy/solver tools share a concurrency limit of two. - **Credential-aware.** A hosted operator may configure provider credentials; the repository does not claim the public instance's current key inventory. Keys are redacted from application logs and envelopes. - Historical automated AI code-review results are documented in [`SECURITY.md`](SECURITY.md#independent-review); they are not a current third-party certification. 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 ```bash uv sync --extra dev --extra analytics # always both extras: dev = pytest/ruff, analytics = the dashboard's GCP libs uv run pytest uv run ruff check . npx @modelcontextprotocol/inspector uv run python -m sportiq.server ``` **Analytics dashboard** (read-only local usage view — Cloud Run / PyPI / GitHub). Same setup as above, then just run it: ```bash uv run python scripts/dashboard.py # writes dashboard.html and opens it; GITHUB_TOKEN optional (Sponsors panel) ``` > Note: the dashboard's HTML template (`scripts/dashboard_template.html`) is currently local-only maintainer tooling, so a fresh clone can't render it yet. **Repository layout:** `src/` is the MCP server (published to PyPI, deployed to Cloud Run); `website/` is the Next.js marketing site deployed to Vercel. The two ship independently — `website/` is excluded from the Python package and the backend container. 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](https://github.com/f1db/f1db)** (CC BY 4.0) — per-circuit stop counts + lap lengths; pit **loss** measured offline from OpenF1 laps. - **[Cricsheet](https://cricsheet.org)** — ball-by-ball IPL data → derived venue scoring priors (`venues.json`). - **[martj42 international football results](https://github.com/martj42/international_results)** (CC0) — Elo backtesting. - **[OpenF1](https://openf1.org)** — keyless live F1 telemetry (runtime source). - **[football-data.org](https://football-data.org)** — free football data (runtime source). ## License & author Created and maintained by **Utkarsh Gupta** ([@Ninjabeam20](https://github.com/Ninjabeam20)). Licensed under the [MIT License](LICENSE) — © 2026 Utkarsh Gupta. Canonical package: [`sportiq-mcp` on PyPI](https://pypi.org/project/sportiq-mcp/) / `io.github.Ninjabeam20/sportiq-mcp` in the [official MCP registry](https://registry.modelcontextprotocol.io).