__init__.py•1.69 kB
"""
Gurddy MCP Server - Model Context Protocol server for optimization problems.
This package provides a complete MCP server implementation for solving
Constraint Satisfaction Problems (CSP), Linear Programming (LP), and
Game Theory problems using the Gurddy optimization library.
Features:
- CSP: N-Queens, Graph/Map Coloring, Sudoku, Logic Puzzles, Scheduling
- LP/MIP: Linear Programming, Production Planning, Portfolio Optimization
- Game Theory: Minimax, Zero-Sum Games, Robust Optimization
- Dual Transport: Stdio (IDE integration) and HTTP/SSE (web clients)
- Command-line tools and Python API
Usage:
# As MCP stdio server (for IDE integration)
gurddy-mcp
# Run examples
python -m mcp_server.server run-example minimax
# HTTP API server
uvicorn mcp_server.mcp_http_server:app --host 0.0.0.0 --port 8080
# Direct import
from mcp_server.handlers.gurddy import solve_minimax_game
result = solve_minimax_game([[0, -1, 1], [1, 0, -1], [-1, 1, 0]], player="row")
"""
__version__ = "0.1.0"
__author__ = "Gurddy MCP Team"
__email__ = "contact@example.com"
# Import main components for easy access
from mcp_server.handlers.gurddy import (
solve_n_queens,
solve_graph_coloring,
solve_map_coloring,
solve_sudoku,
solve_lp,
solve_csp_generic,
solve_production_planning,
solve_minimax_game,
solve_minimax_decision,
info,
run_example,
)
__all__ = [
"solve_n_queens",
"solve_graph_coloring",
"solve_map_coloring",
"solve_sudoku",
"solve_lp",
"solve_csp_generic",
"solve_production_planning",
"solve_minimax_game",
"solve_minimax_decision",
"info",
"run_example",
]