How to Use the Trimble MCP in AutoGen

Q: Can AutoGen and the MCP Server handle multiple routing options for Trimble?

Yes. You can set up agents that compare outputs from calculatematrixrouting against compliant routes derived from calculatetruckroute, forcing a deliberation on the optimal choice.

Q: Is the AutoGen MCP Server good for validating multiple endpoints for Trimble?

It is. You can task two agents: one runs calculatematrixrouting and another uses searchtrimbleaddress to validate every single origin/destination, ensuring accuracy.

Q: Does the AutoGen MCP Server assist with complex area analysis for Trimble?

It can. By using calculatedrivingisochrone, you provide a boundary map, and agents can then debate whether that area is commercially viable based on other data points.

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Create your Vinkius account to connect Trimble to AutoGen and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Trimble with AutoGen

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MCP Server for Debating Route Compliance

When you need agents to debate the best route, start by giving them `get_truck_directions`. One agent can argue for speed, while another checks compliance using `route_by_vehicle_size`. The system forces a consensus on whether the path works with specific vehicle dimensions. This negotiation process is perfect for AutoGen. Agents challenge each other's assumptions until a single, compliant recommendation emerges.

MCP Server for Multi-Option Feasibility Debate

A core use case is debating the cost versus time of multiple paths. Feed `calculate_matrix_routing` data to one agent and let another evaluate potential expenses using `calculate_trip_tolls`. The agents must debate which combination offers the best overall value. This system moves beyond simple calculation; it forces deliberation between competing operational perspectives.

MCP Server for Conflict Resolution in Geocoding

If an agent gets a coordinate, another agent must validate it. They can use `reverse_geocode` to get the commercial address and then cross-check that location using `search_trimble_address`. This process resolves ambiguity between raw coordinates and validated points. It's perfect for AutoGen: one agent suggests a point; another verifies its existence in the Trimble database.

Setup guide

Set up Trimble MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Trimble tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Trimble_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Trimble data")
print(result.messages[-1].content)

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Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Trimble_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Trimble data")
    print(result.messages[-1].content)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Trimble. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Trimble MCP in AutoGen

The server enables your multi-agent system to debate complex logistical decisions. Agents can challenge each other on compliance, cost, or feasibility using specific tools from Trimble.

Yes. You can set up agents that compare outputs from `calculate_matrix_routing` against compliant routes derived from `calculate_truck_route`, forcing a deliberation on the optimal choice.

The server handles geographic coordinates, mileage figures, and dimensional constraints (like height/weight). This allows agents to debate feasibility using these concrete metrics.

It is. You can task two agents: one runs `calculate_matrix_routing` and another uses `search_trimble_address` to validate every single origin/destination, ensuring accuracy.

It can. By using `calculate_driving_isochrone`, you provide a boundary map, and agents can then debate whether that area is commercially viable based on other data points.

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