Gurddy MCP Server

""" Tool definitions - only basic metadata, schemas auto-generated from functions. This is the single source of truth for tool metadata. """ from typing import List, Dict, Any # Basic tool definitions - schemas will be auto-generated TOOL_DEFINITIONS = [ { "name": "info", "function": "info", "description": "Get information about the gurddy package", "category": "meta", "module": "handlers.gurddy" }, { "name": "install", "function": "pip_install", "description": "Install or upgrade the gurddy package", "category": "meta", "module": "handlers.gurddy" }, { "name": "run_example", "function": "run_example", "description": "Run a gurddy example (lp, csp, n_queens, graph_coloring, map_coloring, scheduling, logic_puzzles, optimized_csp, optimized_lp, minimax, scipy_optimization, classic_problems)", "category": "examples", "module": "handlers.gurddy" }, { "name": "solve_n_queens", "function": "solve_n_queens", "description": "Solve the N-Queens problem", "category": "csp", "module": "handlers.gurddy" }, { "name": "solve_sudoku", "function": "solve_sudoku", "description": "Solve a 9x9 Sudoku puzzle", "category": "csp", "module": "handlers.gurddy" }, { "name": "solve_graph_coloring", "function": "solve_graph_coloring", "description": "Solve graph coloring problem", "category": "csp", "module": "handlers.gurddy" }, { "name": "solve_map_coloring", "function": "solve_map_coloring", "description": "Solve map coloring problem", "category": "csp", "module": "handlers.gurddy" }, { "name": "solve_lp", "function": "solve_lp", "description": "Solve a Linear Programming (LP) or Mixed Integer Programming (MIP) problem using PuLP", "category": "optimization", "module": "handlers.gurddy" }, { "name": "solve_production_planning", "function": "solve_production_planning", "description": "Solve a production planning optimization problem with optional sensitivity analysis", "category": "optimization", "module": "handlers.gurddy" }, { "name": "solve_minimax_game", "function": "solve_minimax_game", "description": "Solve a two-player zero-sum game using minimax (game theory)", "category": "game_theory", "module": "handlers.gurddy" }, { "name": "solve_minimax_decision", "function": "solve_minimax_decision", "description": "Solve a minimax decision problem under uncertainty (robust optimization)", "category": "game_theory", "module": "handlers.gurddy" }, { "name": "solve_24_point_game", "function": "solve_24_point_game", "description": "Solve 24-point game with four numbers using arithmetic operations", "category": "classic", "module": "handlers.gurddy" }, { "name": "solve_chicken_rabbit_problem", "function": "solve_chicken_rabbit_problem", "description": "Solve classic chicken-rabbit problem with heads and legs constraints", "category": "classic", "module": "handlers.gurddy" }, { "name": "solve_scipy_portfolio_optimization", "function": "solve_scipy_portfolio_optimization", "description": "Solve nonlinear portfolio optimization using SciPy", "category": "scipy", "module": "handlers.gurddy" }, { "name": "solve_scipy_statistical_fitting", "function": "solve_scipy_statistical_fitting", "description": "Solve statistical parameter estimation using SciPy", "category": "scipy", "module": "handlers.gurddy" }, { "name": "solve_scipy_facility_location", "function": "solve_scipy_facility_location", "description": "Solve facility location problem using hybrid CSP-SciPy approach", "category": "scipy", "module": "handlers.gurddy" }, ]