How to Use the Haversine Distance Engine MCP in Google ADK

Feed exact coordinate distances into your long-context Gemini agents with the Google ADK.

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Connect Haversine Distance Engine MCP to Google ADK

Create your Vinkius account to connect Haversine Distance Engine to Google ADK 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 Haversine Distance Engine with Google ADK

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Query coordinates inside enterprise BigQuery pipelines

Enterprise data often lives in BigQuery tables. Connecting this Google ADK toolset lets your agents pull raw coordinate pairs from your database and compute real distances using `calculate_distance` on the fly. This setup lets you process millions of rows of location data via MCP tools. Your agent coordinates the database pull and the distance math without leaving your Google Cloud environment.

Long-context spatial reasoning with Gemini

Gemini models can hold massive context windows, allowing them to analyze entire shipping manifests at once. This MCP Server lets the model scan a list of addresses and trigger `calculate_distance` to find spatial patterns in your logistics network. Instead of running slow batch scripts, the model handles the analysis and the math in a single turn. You get fast answers to complex routing questions.

Restrict exposed tools in your Google ADK configuration

Sometimes you only want an agent to calculate distances. The Google ADK lets you filter the toolset, exposing only `calculate_distance` while hiding other server capabilities. This restriction prevents your agent from executing unauthorized actions over the MCP protocol. It keeps your enterprise application secure and focused on its specific spatial task.

Setup guide

Set up Haversine Distance Engine MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with Haversine Distance Engine tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="Haversine Distance Engine_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Haversine Distance Engine tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Haversine Distance Engine MCP in Google ADK

Initialize the server parameters with your HTTP endpoint and pass the toolset to your agent. The framework handles the connection details so your Gemini model can use the tool immediately.

Yes, you can deploy the agent to Vertex AI. The toolset integrates with Google Cloud infrastructure, allowing secure execution of your distance math.

Yes, it supports both stdio and HTTP transports for your MCP client. You can run the server locally during development and switch to cloud-hosted HTTP for your production runs.

When you pass coordinates to your Gemini agent, it recognizes the need for spatial math. It automatically calls the tool to get the real-world distance instead of guessing.

The engine operates in a secure, isolated sandbox on Google Cloud. Your latitude and longitude parameters are processed in-memory and immediately destroyed once the calculation completes.

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