Gurddy MCP Server

""" Central registry for all MCP tools and their metadata. This is the single source of truth for tool definitions. NOTE: Schemas are auto-generated from function signatures. Run `python scripts/generate_registry.py` to update. """ from typing import List, Dict, Any # Tool definitions - single source of truth # Schemas auto-generated from function signatures TOOLS = [ { "name": "info", "function": "info", "description": "Get information about the gurddy package", "category": "meta", "module": "handlers.gurddy", "inputSchema": { "type": "object", "properties": {}, "required": [] } }, { "name": "install", "function": "pip_install", "description": "Install or upgrade the gurddy package", "category": "meta", "module": "handlers.gurddy", "inputSchema": { "type": "object", "properties": { "package": { "type": "string", "description": "Parameter package" }, "upgrade": { "type": "boolean", "description": "Parameter upgrade" } }, "required": [ "package" ] } }, { "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", "inputSchema": { "type": "object", "properties": { "example_name": { "type": "string", "description": "Parameter example_name" } }, "required": [ "example_name" ] } }, { "name": "solve_n_queens", "function": "solve_n_queens", "description": "Solve the N-Queens problem", "category": "csp", "module": "handlers.gurddy", "inputSchema": { "type": "object", "properties": { "n": { "type": "integer", "description": "Parameter n" } }, "required": [] } }, { "name": "solve_sudoku", "function": "solve_sudoku", "description": "Solve a 9x9 Sudoku puzzle", "category": "csp", "module": "handlers.gurddy", "inputSchema": { "type": "object", "properties": { "puzzle": { "type": "array", "items": { "type": "array", "items": { "type": "integer" } }, "description": "Parameter puzzle" } }, "required": [ "puzzle" ] } }, { "name": "solve_graph_coloring", "function": "solve_graph_coloring", "description": "Solve graph coloring problem", "category": "csp", "module": "handlers.gurddy", "inputSchema": { "type": "object", "properties": { "edges": { "type": "array", "items": { "type": "array", "items": { "type": "integer" } }, "description": "Parameter edges" }, "num_vertices": { "type": "integer", "description": "Parameter num_vertices" }, "max_colors": { "type": "integer", "description": "Parameter max_colors" } }, "required": [ "edges", "num_vertices" ] } }, { "name": "solve_map_coloring", "function": "solve_map_coloring", "description": "Solve map coloring problem", "category": "csp", "module": "handlers.gurddy", "inputSchema": { "type": "object", "properties": { "regions": { "type": "array", "items": { "type": "string" }, "description": "Parameter regions" }, "adjacencies": { "type": "array", "items": { "type": "array", "items": { "type": "string" } }, "description": "Parameter adjacencies" }, "max_colors": { "type": "integer", "description": "Parameter max_colors" } }, "required": [ "regions", "adjacencies" ] } }, { "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", "inputSchema": { "type": "object", "properties": { "problem": { "type": "object", "description": "Parameter problem" } }, "required": [ "problem" ] } }, { "name": "solve_production_planning", "function": "solve_production_planning", "description": "Solve a production planning optimization problem with optional sensitivity analysis", "category": "optimization", "module": "handlers.gurddy", "inputSchema": { "type": "object", "properties": { "profits": { "type": "object", "description": "Parameter profits" }, "consumption": { "type": "object", "description": "Parameter consumption" }, "capacities": { "type": "object", "description": "Parameter capacities" }, "integer": { "type": "boolean", "description": "Parameter integer" }, "sensitivity_analysis": { "type": "boolean", "description": "Parameter sensitivity_analysis" } }, "required": [ "profits", "consumption", "capacities" ] } }, { "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", "inputSchema": { "type": "object", "properties": { "payoff_matrix": { "type": "array", "items": { "type": "array", "items": { "type": "number" } }, "description": "Parameter payoff_matrix" }, "player": { "type": "string", "description": "Parameter player" } }, "required": [ "payoff_matrix" ] } }, { "name": "solve_minimax_decision", "function": "solve_minimax_decision", "description": "Solve a minimax decision problem under uncertainty (robust optimization)", "category": "game_theory", "module": "handlers.gurddy", "inputSchema": { "type": "object", "properties": { "scenarios": { "type": "array", "items": { "type": "object" }, "description": "Parameter scenarios" }, "decision_vars": { "type": "array", "items": { "type": "string" }, "description": "Parameter decision_vars" }, "budget": { "type": "number", "description": "Parameter budget" }, "objective": { "type": "string", "description": "Parameter objective" } }, "required": [ "scenarios", "decision_vars" ] } }, { "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", "inputSchema": { "type": "object", "properties": { "numbers": { "type": "array", "items": { "type": "integer" }, "description": "Parameter numbers" } }, "required": [ "numbers" ] } }, { "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", "inputSchema": { "type": "object", "properties": { "total_heads": { "type": "integer", "description": "Parameter total_heads" }, "total_legs": { "type": "integer", "description": "Parameter total_legs" } }, "required": [ "total_heads", "total_legs" ] } }, { "name": "solve_scipy_portfolio_optimization", "function": "solve_scipy_portfolio_optimization", "description": "Solve nonlinear portfolio optimization using SciPy", "category": "scipy", "module": "handlers.gurddy", "inputSchema": { "type": "object", "properties": { "expected_returns": { "type": "array", "items": { "type": "number" }, "description": "Parameter expected_returns" }, "covariance_matrix": { "type": "array", "items": { "type": "array", "items": { "type": "number" } }, "description": "Parameter covariance_matrix" }, "risk_tolerance": { "type": "number", "description": "Parameter risk_tolerance" } }, "required": [ "expected_returns", "covariance_matrix" ] } }, { "name": "solve_scipy_statistical_fitting", "function": "solve_scipy_statistical_fitting", "description": "Solve statistical parameter estimation using SciPy", "category": "scipy", "module": "handlers.gurddy", "inputSchema": { "type": "object", "properties": { "data": { "type": "array", "items": { "type": "number" }, "description": "Parameter data" }, "distribution": { "type": "string", "description": "Parameter distribution" } }, "required": [ "data" ] } }, { "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", "inputSchema": { "type": "object", "properties": { "customer_locations": { "type": "array", "items": { "type": "array", "items": { "type": "number" } }, "description": "Parameter customer_locations" }, "customer_demands": { "type": "array", "items": { "type": "number" }, "description": "Parameter customer_demands" }, "facility_locations": { "type": "array", "items": { "type": "array", "items": { "type": "number" } }, "description": "Parameter facility_locations" }, "max_facilities": { "type": "integer", "description": "Parameter max_facilities" }, "fixed_cost": { "type": "number", "description": "Parameter fixed_cost" } }, "required": [ "customer_locations", "customer_demands", "facility_locations" ] } } ] def get_all_tool_names() -> List[str]: """Get list of all tool names.""" return [tool["name"] for tool in TOOLS] def get_all_function_names() -> List[str]: """Get list of all function names for imports.""" return [tool["function"] for tool in TOOLS] def get_tools_by_category(category: str) -> List[Dict[str, Any]]: """Get tools filtered by category.""" return [tool for tool in TOOLS if tool["category"] == category] def get_tool_count() -> int: """Get total number of tools.""" return len(TOOLS) def get_categories() -> List[str]: """Get list of all categories.""" return list(set(tool["category"] for tool in TOOLS)) def get_tool_schemas() -> Dict[str, Dict[str, Any]]: """Get tool schemas for MCP server registration. Returns: Dict mapping tool name to schema (description + inputSchema) """ schemas = {} for tool in TOOLS: schemas[tool["name"]] = { "description": tool["description"], "inputSchema": tool["inputSchema"] } return schemas def get_tool_by_name(name: str) -> Dict[str, Any]: """Get tool definition by name.""" for tool in TOOLS: if tool["name"] == name: return tool return None def get_function_name_mapping() -> Dict[str, str]: """Get mapping from tool name to function name. Returns: Dict mapping tool name to function name """ return {tool["name"]: tool["function"] for tool in TOOLS} def generate_tool_list_markdown() -> str: """Generate markdown list of all tools for documentation.""" lines = [] for tool in TOOLS: lines.append(f"- `{tool['name']}` - {tool['description']}") return "\n".join(lines) def generate_auto_approve_list() -> List[str]: """Generate list of tool names for MCP auto-approve configuration.""" return get_all_tool_names() # Export commonly used values ALL_TOOL_NAMES = get_all_tool_names() ALL_FUNCTION_NAMES = get_all_function_names() TOOL_COUNT = get_tool_count() TOOL_SCHEMAS = get_tool_schemas() FUNCTION_NAME_MAPPING = get_function_name_mapping()