How to Use the AlisQI MCP in AutoGen

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Connect AlisQI MCP to AutoGen

Create your Vinkius account to connect AlisQI 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 AlisQI with AutoGen

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Perplexity

Debate quality issues in AutoGen

Assign one agent to `list_results` while another critiques the findings. Your agents negotiate the correct interpretation of quality metrics before taking action. This removes the guesswork from result analysis. You build a system where agents check each other for errors.

Analyze set metadata with AutoGen

Call `get_analysis_set_details` to provide your agents with the context they need to understand a specific dataset. They use this info to structure their debate. It prevents agents from misinterpreting raw numbers. They know exactly what they are looking at before they start talking.

Manage results through AutoGen agents

Use `store_results` to execute updates once your agents reach a consensus. You define the rules, and the agents handle the data entry. It ensures that only verified results get pushed back to your system. The deliberation process acts as a final gatekeeper.

Setup guide

Set up AlisQI 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 AlisQI 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="AlisQI_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

    result = await agent.run("List recent AlisQI 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 AlisQI. 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.

Why Choose Vinkius

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Common questions about AlisQI MCP in AutoGen

The MCP tools are passed to your agents as functions. They call these tools during their conversation to get data or update records.

Yes. Each agent can call the tools independently as part of their assigned role in the debate.

The server is compatible with standard AutoGen adapters. It provides the tool schemas your agents need to execute functions within the chat.

You install the extension, point to the Vinkius URL, and pass the tools to your AssistantAgent. It handles the schema conversion automatically.

The connection is isolated and ephemeral. No records are stored by the server; it simply acts as a bridge for your agents to fetch or write the data you authorize.

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