Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@IPL MCP ServerShow me Virat Kohli's batting stats"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
IPL MCP Server
A Model Context Protocol (MCP) server that provides natural language access to IPL (Indian Premier League) cricket match data. Built using data from Cricsheet with an enhanced sample of 18 IPL matches including Virat Kohli games and CSK vs MI classics.
š Features
Natural Language Queries: Ask questions about IPL data in plain English
Enhanced Dataset: 18 carefully selected IPL matches including:
Virat Kohli batting performances (99 runs in 4 matches)
CSK vs MI classic encounters (3 matches)
All major IPL teams represented
Rich Analytics: Player stats, team performance, match analysis
Claude Desktop Integration: Works seamlessly with Claude Desktop
Fast SQL Backend: Efficient SQLite database with optimized queries
Extensible: Can easily be extended to work with the full 1,169+ match dataset
š Quick Start
Prerequisites
Python 3.11+
uvpackage managerClaude Desktop (for MCP integration)
Installation
Clone and setup:
Install dependencies:
Setup database and load data:
This will:
Create SQLite database tables
Process 18 sample JSON match files (includes V Kohli & CSK vs MI)
Calculate player and team statistics
Takes ~10-15 seconds to complete
Test the queries (optional):
Start the MCP server:
šÆ Example Queries
Basic Match Information
"Show me all matches in the dataset"
"How many matches are in the database?"
"Which team won the most matches?"
"What was the highest total score?"
"Show matches played in Mumbai"
Player Performance
"Who scored the most runs across all matches?"
"Which bowler took the most wickets?"
"Show me Virat Kohli's batting stats"
"Who has the best bowling figures in a single match?"
"Show all centuries scored"
Advanced Analytics
"What's the average first innings score?"
"Which venue has the highest scoring matches?"
"What's the most successful chase target?"
"Which team has the best powerplay performance?"
"Show me partnership records over 100 runs"
Match-Specific Queries
"Show me the scorecard for match between CSK and MI"
"How many sixes were hit in the final?"
"What was the winning margin in the closest match?"
š§ Claude Desktop Integration
Add to Claude Desktop config:
Edit your Claude Desktop MCP configuration file:
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%/Claude/claude_desktop_config.json
Restart Claude Desktop
Test the connection: Ask Claude: "Show me IPL team statistics"
š Database Schema
The server uses SQLite with the following key tables:
matches: Match metadata (teams, venue, date, outcome)
innings: Innings-level data (totals, wickets, overs)
deliveries: Ball-by-ball data (runs, wickets, extras)
player_stats: Aggregated batting/bowling statistics
team_stats: Team performance metrics
players: Player registry with Cricsheet IDs
teams: Team information
š ļø Advanced Usage
Command Line Options
API Integration
The server can be extended to work with other MCP clients beyond Claude Desktop. The query engine supports pattern matching for natural language understanding.
Adding Custom Queries
Extend the QueryEngine class in src/mcp_server/query_engine.py:
š Performance
Database Size: ~3MB for 18 sample matches
Setup Time: 10-15 seconds for data load
Query Response: <1 second for most queries
Memory Usage: ~50MB typical runtime
š Scaling to Full Dataset
The system can easily handle the complete 1,169 match dataset:
Full Database Size: ~50MB
Full Setup Time: 2-3 minutes
Simply use
--data-dir datainstead of--data-dir data_small
š Sample Query Results
Query: "Which team won the most matches?"
Query: "Show me Virat Kohli batting stats"
šļø Data Source
All data comes from Cricsheet, which provides:
Ball-by-ball data for IPL matches from 2008-2017 seasons (enhanced sample of 18 matches)
Player registry with unique identifiers
Match metadata including officials, venues, outcomes
JSON format with comprehensive match details
Full dataset available: 1,169+ matches (2008-2024) can be loaded by using
--data-dir data
š¤ Contributing
Fork the repository
Create a feature branch
Add your improvements
Test with sample queries
Submit a pull request
š License
This project is licensed under the MIT License. Data provided by Cricsheet under their terms of use.
š Working with Full Dataset
To use the complete 1,169 match dataset instead of the sample:
Reset and load full data:
ā ļø This will take 2-3 minutes to complete
Benefits of full dataset:
Complete IPL history (2008-2024)
More accurate player statistics
Comprehensive team performance data
Better trend analysis capabilities
ā Verify Installation
Test your setup with these commands:
š Links
Cricsheet - Data source
Claude Desktop - MCP client
MCP Protocol - Protocol specification
Built with ā¤ļø for cricket analytics and AI-powered data exploration