How to Use the Haversine Distance Engine MCP in AutoGen

Let your AutoGen agents debate and calculate distances using the Haversine Distance Engine.

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Connect Haversine Distance Engine MCP to AutoGen

Create your Vinkius account to connect Haversine Distance Engine 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 Haversine Distance Engine with AutoGen

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Claude

Perplexity

Consensus on geographic distance

Your AutoGen agents use `calculate_distance` to verify routes during their internal discussions. One agent proposes a path, and another validates the distance. This prevents errors in complex logistics planning. You get a group-vetted result based on the Haversine formula.

Multi-agent negotiation with MCP

The `calculate_distance` tool acts as a shared source of truth for your agents. They use it to resolve disagreements about transport costs. This forces your agents to base their decisions on hard numbers. It adds a layer of objective reality to their debates.

Dynamic tool adaptation

AutoGen automatically converts the MCP schema for `calculate_distance` into a usable agent tool. You plug it in and it just works. It supports complex multi-agent conversations without requiring extra glue code. Your agents share the tool capability instantly.

Setup guide

Set up Haversine Distance Engine 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 Haversine Distance Engine 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="Haversine Distance Engine_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Haversine Distance Engine 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="Haversine Distance Engine_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

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

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Haversine Engine. 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 Haversine Distance Engine MCP in AutoGen

Yes. Once you register the server, all agents in your group chat can call the tool to resolve distance-based queries.

Agents can call the tool to verify distance claims made by peers. If the math doesn't align, the agents adjust their conclusions accordingly.

It provides consistent spherical calculations every time. You can trust the tool to deliver the same result across different agent sessions.

The server is built for high-throughput environments. It handles multiple concurrent requests from your agents without performance degradation.

The server runs in a zero-trust sandbox. Your input coordinates are never stored or logged, ensuring your location data remains private.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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