Smolagents Integration

Use case: Lightweight agents with geospatial capabilities (Hugging Face)

Smolagents is Hugging Face's simple, efficient agent framework. Perfect for deploying geospatial agents with minimal overhead.

from smolagents import CodeAgent, Tool, HfApiModel
import requests
import os

class MapboxMCP:
    """Mapbox MCP connector."""

    def __init__(self, token: str = None):
        self.url = 'https://mcp.mapbox.com/mcp'
        token = token or os.getenv('MAPBOX_ACCESS_TOKEN')
        self.headers = {
            'Content-Type': 'application/json',
            'Authorization': f'Bearer {token}'
        }

    def call_tool(self, tool_name: str, params: dict) -> str:
        request = {
            'jsonrpc': '2.0',
            'id': 1,
            'method': 'tools/call',
            'params': {'name': tool_name, 'arguments': params}
        }
        response = requests.post(self.url, headers=self.headers, json=request)
        result = response.json()['result']
        return result['content'][0]['text']

# Create Mapbox tools for Smolagents
class DirectionsTool(Tool):
    name = "directions_tool"
    description = """
    Get driving directions between two locations.

    Args:
        origin: Origin coordinates as [longitude, latitude]
        destination: Destination coordinates as [longitude, latitude]

    Returns:
        Directions with distance and travel time
    """

    def __init__(self):
        super().__init__()
        self.mcp = MapboxMCP()

    def forward(self, origin: list, destination: list) -> str:
        return self.mcp.call_tool('directions_tool', {
            'coordinates': [
                {'longitude': origin[0], 'latitude': origin[1]},
                {'longitude': destination[0], 'latitude': destination[1]}
            ],
            'routing_profile': 'mapbox/driving-traffic'
        })

class CalculateDistanceTool(Tool):
    name = "distance_tool"
    description = """
    Calculate distance between two points (offline, instant).

    Args:
        from_coords: Start coordinates [longitude, latitude]
        to_coords: End coordinates [longitude, latitude]
        units: 'miles' or 'kilometers'

    Returns:
        Distance as a number
    """

    def __init__(self):
        super().__init__()
        self.mcp = MapboxMCP()

    def forward(self, from_coords: list, to_coords: list, units: str = 'miles') -> str:
        return self.mcp.call_tool('distance_tool', {
            'from': {'longitude': from_coords[0], 'latitude': from_coords[1]},
            'to': {'longitude': to_coords[0], 'latitude': to_coords[1]},
            'units': units
        })

class SearchPOITool(Tool):
    name = "search_poi"
    description = """
    Search for points of interest by category.

    Args:
        category: POI category (restaurant, hotel, gas_station, etc.)
        location: Search center [longitude, latitude]

    Returns:
        List of nearby POIs with names and coordinates
    """

    def __init__(self):
        super().__init__()
        self.mcp = MapboxMCP()

    def forward(self, category: str, location: list) -> str:
        return self.mcp.call_tool('category_search_tool', {
            'category': category,
            'proximity': {'longitude': location[0], 'latitude': location[1]}
        })

class IsochroneTool(Tool):
    name = "isochrone_tool"
    description = """
    Calculate reachable area within time limit (isochrone).

    Args:
        location: Center point [longitude, latitude]
        minutes: Time limit in minutes
        profile: 'mapbox/driving', 'mapbox/walking', or 'mapbox/cycling'

    Returns:
        GeoJSON polygon of reachable area
    """

    def __init__(self):
        super().__init__()
        self.mcp = MapboxMCP()

    def forward(self, location: list, minutes: int, profile: str = 'mapbox/driving') -> str:
        return self.mcp.call_tool('isochrone_tool', {
            'coordinates': {'longitude': location[0], 'latitude': location[1]},
            'contours_minutes': [minutes],
            'profile': profile
        })

# Create agent with Mapbox tools
model = HfApiModel()

agent = CodeAgent(
    tools=[
        DirectionsTool(),
        CalculateDistanceTool(),
        SearchPOITool(),
        IsochroneTool()
    ],
    model=model
)

# Use agent
result = agent.run(
    "Find restaurants within 10 minutes walking from Times Square NYC "
    "(coordinates: -73.9857, 40.7484). Calculate distances to each."
)

print(result)

Real-world example - Property search agent:

class PropertySearchAgent:
    def __init__(self):
        self.mcp = MapboxMCP()

        # Create specialized tools
        tools = [
            IsochroneTool(),
            SearchPOITool(),
            CalculateDistanceTool()
        ]

        self.agent = CodeAgent(
            tools=tools,
            model=HfApiModel()
        )

    def find_properties_near_work(
        self,
        work_location: list,
        max_commute_minutes: int,
        property_locations: list[dict]
    ):
        """Find properties within commute time of work."""

        prompt = f"""
        I need to find properties within {max_commute_minutes} minutes
        driving of my work at {work_location}.

        Property locations to check:
        {property_locations}

        For each property:
        1. Calculate if it's within the commute time
        2. Find nearby amenities (grocery stores, restaurants)
        3. Calculate distances to key locations

        Return a ranked list of properties with commute time and nearby amenities.
        """

        return self.agent.run(prompt)

# Usage
property_agent = PropertySearchAgent()

properties = [
    {'id': 1, 'address': '123 Main St', 'coords': [-122.4194, 37.7749]},
    {'id': 2, 'address': '456 Oak Ave', 'coords': [-122.4094, 37.7849]},
]

results = property_agent.find_properties_near_work(
    work_location=[-122.4, 37.79],  # Downtown SF
    max_commute_minutes=30,
    property_locations=properties
)

Benefits:

• Lightweight and efficient
• Simple tool definition
• Code-based agent execution
• Great for production deployment