🏏 Cricket MCP Server

Cricket analytics for Claude Desktop, Claude Code, Cursor and any other MCP client — a calibrated win-probability model, 22,479 archived matches, and live prediction-market prices.

A Model Context Protocol server that gives AI assistants real cricket knowledge: a calibrated win-probability model, a ball-by-ball archive of 22,000+ matches, live prediction-market prices, career records, and live scores.

Ask cricket questions in plain language and get answers computed from data rather than recalled from training.

⚡ Add it in one step

It is hosted. There is nothing to install, download, build or configure.

https://cricketfornoobs.com/mcp

Paste that into your client's connector settings and you are done.

No account, no API key, no data pipeline. Read-only.

Prefer to run it on your own machine? See Quick start below: same tools, one static binary.

Related MCP server: cricket-mcp

💬 Things to ask it

• "Who's winning the India match right now, and what does the model say?"

• "Who is favoured at 149 for 7 chasing 178 with three overs left?"

• "How does Kohli bat against Bumrah in T20s?"

• "What does the market think versus your model for Welsh Fire vs Southern Brave?"

• "How does Bumrah get his wickets — bowled, caught, lbw?"

• "What's Rashid Khan's dot-ball percentage in T20s?"

• "Is Kohli better batting first or chasing?"

• "Who does Rohit Sharma score most of his runs with?"

• "Does Grand Prairie Stadium favour chasing?"

• "Show me Pooran's death-overs record."

• "What actually is a googly?"

The same win model runs in production at cricketfornoobs.com, a live cricket explainer for American sports fans. This server exposes the analytics side of it to any MCP client.

✨ What makes this different

Most sports MCP servers wrap a scores API. This one ships analysis:

• Win probability from a fitted model — logistic regression per format and innings over 10,847 matches (3.4M ball states), with pre-match Elo ratings. Held-out log loss 0.42 (T20 chases) / 0.40 (ODI chases); ~91% accurate on confident calls. It knows that 149/7 chasing 178 is not the same story as 149/2.

• Ball-by-ball archive — 22,479 matches and 11.4M deliveries across T20, ODI/List-A, Tests and domestic multi-day cricket.

• Career and matchup records — batter-vs-bowler head-to-heads, phase splits (powerplay / middle / death), venue reports, league leaderboards.

• Baseball translations — every cricket term explained through its closest baseball equivalent, for newcomers to the sport.

🛠️ Tools

All tools are read-only.

🚀 Quick start

1. Install

One static binary, no runtime, no interpreter, no dependencies.

go install github.com/asaraog/mcp-cricket/cmd/cricket-mcp@latest

Or download a prebuilt binary for macOS (Apple silicon or Intel), Linux (x86-64 or arm64) or Windows from Releases.

Register it with Claude Code:

claude mcp add cricket -- ~/go/bin/cricket-mcp

2. Or configure a desktop client

Add the server to your client's config — for Claude Desktop:

{
  "mcpServers": {
    "cricket": {
      "command": "/ABSOLUTE/PATH/TO/cricket-mcp"
    }
  }
}

Restart the client and the cricket tools appear. That's the whole setup — on first use the server downloads the prebuilt archive once (~200 MB) into your OS cache directory (~/Library/Caches on macOS, ~/.cache on Linux, %LocalAppData% on Windows) and reuses it from then on. No account, no API key, no data pipeline to run.

The archive is generated from public Cricsheet data, so you can build your own rather than downloading ours:

curl -O https://cricsheet.org/downloads/all_json.zip
python3 scripts/histgen.py all_json.zip history.db

Then point HISTORY_DB at the result. Limited-overs-only archives work too — tools degrade gracefully when a format is absent.

⚙️ Configuration

Live-score tools work without any archive; archive tools report clearly when the database is missing rather than inventing an answer.

📊 About the model

The win model is fitted offline, not guessed at runtime. Features are match state (runs, wickets, balls remaining, required rate), pre-match Elo, and a wickets × required-rate interaction — because thin batting hurts far more when the asking rate is steep. Calibration is measured by wickets in hand: within about one point across most of the range.

Par is per ground. A first-innings score only means something relative to what the ground usually yields, so the innings-one segments are fitted against a table of 371 grounds and 7 leagues rather than one global constant. Real pars run from 153.7 to 172.5 by league alone, and further by ground. Pass venue (and league) to cricket_win_probability and the same 80/2 at ten overs is 47% at Chinnaswamy and 60% at Newlands. Without a venue it falls back ground → league → global, which costs about 0.006 of held-out log loss.

It cannot see injuries, weather, pitch reports or team news.

📈 Markets

cricket_market_odds reads public prices from Kalshi, a CFTC-regulated US exchange where contracts settle at $1 and a price in cents is the implied probability. Put beside cricket_win_probability, the gap between the two is the edge a trader would be claiming.

This is informational only — read-only market data, no account, no orders, no advice. The model cannot see injuries, weather or team news, which is often exactly why it disagrees with the market. Event contracts are legal in some jurisdictions and not others.

🙏 Data

Ball-by-ball data from Cricsheet, licensed CC BY-SA 4.0. Live scores from public ESPNcricinfo endpoints; market prices from Kalshi's public API. This project is unaffiliated with any of them.

📝 License

BSD 3-Clause. See LICENSE.