TomTom MCP Server

# Code based on smolagents example from: https://github.com/huggingface/smolagents/blob/main/examples/agent_from_any_llm.py import os from mcp import StdioServerParameters from smolagents import ( CodeAgent, InferenceClientModel, OpenAIServerModel, TransformersModel, tool, ToolCollection, AzureOpenAIServerModel ) from dotenv import load_dotenv load_dotenv() # Choose which inference type to use or add any other from the smolagents library! available_inferences = ["inference_client", "transformers", "openai"] chosen_inference = "inference_client" #chosen_inference = "openai" print(f"Chose model: '{chosen_inference}'") if chosen_inference == "inference_client": model = InferenceClientModel(model_id="meta-llama/Llama-3.2-1B-Instruct", provider="auto") elif chosen_inference == "openai": model = AzureOpenAIServerModel(model_id="your-deployment-id", azure_endpoint="your-azure-endpoint", api_key="your-azure-key", api_version="your-api-version") elif chosen_inference == "transformers": model = TransformersModel(model_id="HuggingFaceTB/SmolLM2-1.7B-Instruct", device_map="auto", max_new_tokens=1000) # Make sure there is an access token available if os.environ.get("TOMTOM_API_KEY", None) is None: raise EnvironmentError("To use TomTom MCP you need to export `TOMTOM_API_KEY` environmental variable.") # Run server with node server_parameters = StdioServerParameters( command="npx", args=["-y", "@tomtom-org/tomtom-mcp@latest"], env={ "TOMTOM_API_KEY": "<your_API_KEY>"}, # replace with your TomTom API key ) # Connect to MCP, create agent with MCP's tool and run it with ToolCollection.from_mcp(server_parameters, trust_remote_code=True) as tool_collection: print("check") for tool in tool_collection.tools: print(f"- {tool.name}") agent = CodeAgent(tools=tool_collection.tools, model=model, verbosity_level=2, stream_outputs=True) print("CodeAgent:", agent.run("What is the reachable range from Amsterdam within 30 minutes by car?")) # Try out different questions!