How to Use the Judge.me MCP in AutoGen

Q: How do I initialize Judge.me in AutoGen?

Install autogen-extmcp and use mcpservertools with a StreamableHttpServerParams URL. The adapter handles the schema conversion automatically for this MCP Server.

Q: How do AutoGen agents handle Judge.me media?

They use listmedias to pull image and video URLs. A vision-capable agent analyzes the media while a text agent reads the review body.

Q: What happens when AutoGen agents query Judge.me products?

They use getproduct to pull specific performance summaries. This allows them to ground their debates in actual sales and review metrics.

Let your AutoGen agents debate customer feedback and manage Q&A workflows using the Judge.me MCP Server.

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Connect Judge.me MCP to AutoGen

Create your Vinkius account to connect Judge.me 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 Judge.me with AutoGen

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Perplexity

AutoGen agents debate review sentiment

The `list_reviews` tool hands your multi-agent conversation raw product feedback to dissect via the MCP connection. A sentiment agent reads the ratings, while a risk agent flags aggressive language. They debate the severity of the feedback. If they disagree, one agent calls `get_review` to pull deeper metadata and moderation status to prove their point before reaching a consensus.

Negotiate customer Q&A responses

`list_questions` provides a backlog of customer inquiries for your agents to resolve. A support agent drafts a reply, but a compliance agent reviews it to ensure it matches company policy. Before finalizing the reply, an agent triggers `get_question` to verify the exact phrasing of the original user. Once they agree, they check `list_answers` to ensure the query is fully resolved.

Audit catalog and incentive programs

Running the MCP tool `list_products` gives your agents the aggregate review counts across your entire store. A marketing agent argues for pushing a specific item, while a sales agent checks the numbers. If they decide to run a campaign, they call `list_coupons` to find active review incentives. They also run `get_settings` to audit how the review widgets and email requests are currently configured.

Setup guide

Set up Judge.me 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 Judge.me 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="Judge.me_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

Get your connection token →

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="Judge.me_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

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

Install `autogen-ext[mcp]` and use `mcp_server_tools` with a `StreamableHttpServerParams` URL. The adapter handles the schema conversion automatically for this MCP Server.

Yes. One agent fetches the data, proposes a moderation action, and requires a second agent's approval before proceeding.

They use `list_medias` to pull image and video URLs. A vision-capable agent analyzes the media while a text agent reads the review body.

They use `get_product` to pull specific performance summaries. This allows them to ground their debates in actual sales and review metrics.

The server processes raw customer questions, review bodies, and discount codes. Because the connection is ephemeral and stateless, no persistent records of your API keys or customer data remain on the MCP Server after the execution completes.

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