Boggle Solver

About

This Python project offers a suite of tools for the classic Boggle word game, demonstrating advanced programming concepts. It leverages a highly efficient Trie data structure for rapid prefix lookups and employs constraint-satisfaction with backtracking for combinatorial search problems, such as determining if a word can be formed from Boggle dice. Additionally, it integrates with the Model Context Protocol (MCP) to function as an external tool for large language models, enabling AI-powered workflows to solve Boggle puzzles or validate words directly within chat interfaces.

Key Features

• Provides a standalone Trie data structure for fast dictionary lookups and prefix checking
• Determines if a word can be spelled with official Boggle dice using constraint satisfaction
• Solves Boggle boards using depth-first search and Trie-based prefix pruning
• 0 GitHub stars
• Supports custom word lists and variable board sizes
• Offers an MCP server for seamless integration with large language models

Use Cases

• Quickly finding all valid words on a Boggle board
• Verifying if a given word is valid to be formed using Boggle dice
• Integrating Boggle game logic into AI applications and LLM-powered conversational agents