SUMO-MCP Server

from mcp_tools.rl import find_sumo_rl_scenario_files, list_rl_scenarios, run_rl_training def rl_train_workflow( scenario_name: str, output_dir: str, episodes: int = 5, steps: int = 1000 ) -> str: """ Workflow to train an RL agent on a built-in sumo-rl scenario. 1. Locate scenario files 2. Run training 3. Return summary """ if not scenario_name: return ( "Error: rl_train workflow requires scenario_name.\n" "Hint: Use manage_rl_task(list_scenarios) to list built-in scenarios, " "or use manage_rl_task(train_custom) for custom net/route files." ) net_file, route_file, err = find_sumo_rl_scenario_files(scenario_name) if err: available = list_rl_scenarios() return f"{err}\nAvailable: {available}" return run_rl_training( net_file=net_file, route_file=route_file, out_dir=output_dir, episodes=episodes, steps_per_episode=steps, algorithm="ql" )