How to Use the Wolai MCP in AutoGen

Q: How does AutoGen use Wolai to manage content?

Agents can debate whether they should createpage or modify an existing one. The process involves agents checking the current state using tools like listpages before committing any changes.

Q: Does AutoGen handle complex Wolai data flows?

Yes. If a workflow needs to query user roles (listusers) and then check corresponding page access rights, the agents will debate and execute both steps sequentially.

Achieve consensus decisions with AutoGen and Wolai's MCP Server.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Wolai MCP to AutoGen

Create your Vinkius account to connect Wolai 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.

GDPR Free for Subscribers

Setup Wolai with AutoGen

Ask AI about this MCP

ChatGPT

Claude

Perplexity

MCP Server: Consensus-Driven Decisions

AutoGen lets multiple agents debate the best path forward using Wolai tools. For example, one agent might use `list_users` to check permissions, while another uses `get_workspace_info` to verify scope. The discussion continues until all competing perspectives converge on a single decision that requires several tool calls.

Multi-Agent Workflow

The system doesn't just execute tools; it debates the results. An agent might suggest using `create_page`, but another challenges it, forcing the use of `list_pages` first to prevent duplicates. This is ideal for processes where no single tool call provides a complete or safe answer.

Structured Tool Execution

AutoGen treats every available Wolai tool as an argument in a discussion. The agents decide which tools to run, and the MCP Server handles the execution of `get_database` or `query_database` based on that consensus. The structure is built around deliberation: multiple viewpoints must agree before any action takes place.

Setup guide

Set up Wolai 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 Wolai 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="Wolai_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Wolai now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Wolai MCP in AutoGen

Agents can debate whether they should `create_page` or modify an existing one. The process involves agents checking the current state using tools like `list_pages` before committing any changes.

Yes. If a workflow needs to query user roles (`list_users`) and then check corresponding page access rights, the agents will debate and execute both steps sequentially.

The core function is deliberation. Agents argue over the necessary sequence of tools—like calling `get_database` followed by `query_database`—until a consensus plan emerges.

You can access page content, user lists, and database schemas. The agents use these defined structures for their debate.

The server touches sensitive data like database rows, page details, and workspace information. AutoGen's strength is having multiple agents debate the risk level before any action occurs.

Use it with your favorite AI tools

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

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript