How to Use the Typeform MCP in AutoGen

Q: How do I set up real-time alerts using Typeform and AutoGen?

You use createwebhook with the destination URL. The agent will then trigger this action, simulating a workflow that requires immediate attention.

Q: What information does the MCP Server provide about workspaces for Typeform and AutoGen?

The getworkspacedetails tool gives all agents visibility into the content and forms within an entire workspace, providing necessary context for their discussions.

Q: Can I define the scope of forms for debate with Typeform and AutoGen?

Yes. You start by listing all workspaces via listworkspaces and then using listforms to pinpoint exactly which form IDs are relevant to the agents' discussion.

Q: What data type does this MCP Server touch regarding privacy in Typeform and AutoGen?

The server touches collected responses. When you use listresponses, the output contains raw, user-submitted records that your agents must manage during their deliberation.

Simulate deliberation processes with AutoGen.

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Setup Typeform with AutoGen

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Automate alerts and actions

The `create_webhook` tool lets your agents set up a webhook, specifying a unique tag and destination URL. This triggers an immediate action when a form is submitted. Agents can use this to simulate system responses—for example, the 'fulfillment agent' automatically sending data to a CRM endpoint upon completion.

Review organizational context

You can run `get_workspace_details` to provide all agents with a full overview of which forms belong in which workspace. This defines the scope for their debate. Knowing where everything sits lets the 'security agent' check compliance across multiple collections before making a decision.

Define actionable targets

First, run `list_workspaces` to define the collection of forms in scope. Then, use `list_forms` to generate a list of specific IDs. This provides clear inputs for the agents. This structured process allows your multi-agent system to narrow its focus from general organizational data down to actionable form targets.

Setup guide

Set up Typeform 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 Typeform 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="Typeform_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

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Common questions about Typeform MCP in AutoGen

You use `create_webhook` with the destination URL. The agent will then trigger this action, simulating a workflow that requires immediate attention.

The `get_workspace_details` tool gives all agents visibility into the content and forms within an entire workspace, providing necessary context for their discussions.

Yes. You start by listing all workspaces via `list_workspaces` and then using `list_forms` to pinpoint exactly which form IDs are relevant to the agents' discussion.

Yes. Webhooks allow for real-time alerts, letting your multi-agent system react instantly when a form is submitted or updated.

The server touches collected responses. When you use `list_responses`, the output contains raw, user-submitted records that your agents must manage during their deliberation.

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