How to Use the Userback MCP in AutoGen

Q: Can I query past Userback data using AutoGen?

Yes. You give your agents access to listfeedbacks. They then discuss the contents of those historical records, allowing you to derive complex insights that require multiple viewpoints to validate.

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Connect Userback MCP to AutoGen

Create your Vinkius account to connect Userback 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 Userback with AutoGen

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Debate project scope using the MCP Server.

Give your agents the `list_userback_projects` tool. One agent can check for completeness, while another can verify if key details are present. They debate whether the current set of projects is sufficient. This consensus-driven approach ensures that before any action is taken, multiple perspectives have signed off on the project scope.

Validate feedback quality with AutoGen.

Your agents can use `get_feedback_details` to pull individual records. A 'Quality Agent' might challenge if the screenshot annotation is clear, while a 'Technical Agent' verifies the reported bug details. The result isn't just data; it's a negotiated conclusion about whether that feedback entry is actionable.

Automate user audit with AutoGen.

Let two agents compare what `list_account_users` returns against the requirements. One agent checks for necessary roles, and the other verifies if all accounts have been listed correctly. This system builds a consensus on user coverage, which is much more reliable than running simple sequential calls.

Setup guide

Set up Userback 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 Userback 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="Userback_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

AutoGen lets your agents debate the results from the MCP Server. Instead of just calling `list_feedbacks`, you set up a conversation where different roles challenge and refine the gathered data until consensus is reached.

The Userback server handles user accounts, project metadata, and structured feedback reports. These are perfect inputs for an autonomous agent system that needs to evaluate multiple viewpoints on the same dataset.

Yes. You give your agents access to `list_feedbacks`. They then discuss the contents of those historical records, allowing you to derive complex insights that require multiple viewpoints to validate.

The agent framework handles schema conversion automatically. This means it can take the raw output from the MCP Server and pass it seamlessly into other tools or internal decision-making processes for deliberation.

Because this server touches user account information, you must structure your agent conversation so that sensitive details retrieved via `list_account_users` are only discussed by authorized agents.

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