How to Use the VineRadar MCP in AutoGen

Resolve complex questions about VineRadar using AutoGen multi-agent debate.

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Connect VineRadar MCP to AutoGen

Create your Vinkius account to connect VineRadar 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 VineRadar with AutoGen

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Debating Search Criteria with AutoGen MCP Server

You can set up two agents. Agent A calls `search_vineyards` to find candidates by location. Agent B then challenges that list, using the data from `get_wine_details` to determine if those vineyards actually produce marketable wines. The system converges on a validated list of viable regions.

Multi-Agent Analysis for VineRadar Data

Want to check feasibility? One agent can use `list_wine_varietals` to establish the full range. A second agent uses `check_api_status` to ensure all data endpoints are live before making recommendations. The debate ensures both scope and operational readiness are covered.

Consensus on Wine Recommendations with AutoGen

Set up agents that argue over the best wine. One agent uses `search_wines` for keyword matching. The second agent cross-references those results using `get_vineyard_details` to confirm the regional source. The final conclusion is a recommendation backed by multiple data points.

Setup guide

Set up VineRadar 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 VineRadar 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="VineRadar_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent VineRadar 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="VineRadar_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent VineRadar 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 VineRadar. 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 VineRadar MCP in AutoGen

The agents debate the conflict. For instance, one agent might find a wine in `search_wines`, but another checks `get_vineyard_details` and flags that the region is unsuitable. The final output resolves this tension.

The core data type debated is the list of supported wine varietals, pulled from `list_wine_varietals`. The agents challenge each other on which varietal combination makes the most sense.

Yes. You can run a process where one agent gets wine details using `get_wine_details`, and another uses that output to determine if it meets specific vintage requirements, effectively auditing the data.

The multi-agent structure forces deliberation. It doesn't just run a tool; agents challenge each other until consensus is reached on the most accurate summary of the available wine and vineyard data.

The framework handles schema conversion automatically, so you just pass the list of tools—like `search_wines` and `search_vineyards`—to the AssistantAgent constructor. It manages the rest.

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