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How to Use the Typeform MCP in OpenAI Agents SDK

Build production agents for Typeform: Connect your OpenAI Agents SDK to structured form data.

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OpenAI Agents SDK

Connect Typeform MCP to OpenAI Agents SDK

Create your Vinkius account to connect Typeform to OpenAI Agents SDK 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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Manage Form Webhooks with the MCP Server

You can create or update a form webhook using `create_webhook`. This lets your agent receive real-time alerts when a specific Typeform is submitted. It also handles listing all webhooks for a given form via `list_webhooks`, so you don't lose track of where submissions are going.

Audit Form Responses with the MCP Server

The agent can check every collected response using `list_responses`. You filter these responses by a specific date range (since) or completion status. If you need to know which forms exist, running `list_forms` gives you all the necessary form IDs to start retrieving data.

Map Out Your Organization's Forms

To see what collections of forms are available, run `list_workspaces`. This shows all Typeform workspaces in your account. Furthermore, you can get details for a specific workspace using `get_workspace_details` to understand the full scope of forms contained within it.

Setup guide

Set up Typeform MCP in OpenAI Agents SDK

Prerequisites

  • Python 3.10+ installed
  • openai-agents package (pip install openai-agents)
  • Active Vinkius subscription with a valid endpoint token
  1. 1

    Install the SDK

    Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.

  2. 2

    Connect via SSE transport

    Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all Typeform tools at runtime.

  3. 3

    Create your Agent

    Pass the MCP to Agent(mcp_servers=[server]). The agent receives Typeform tools as native definitions — JSON schemas resolve automatically.

  4. 4

    Run the agent

    Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Typeform tools and returns structured results. Copy the full example on the right to get started.

agent.py
import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="Typeform Agent",
            instructions="You have access to Typeform tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Typeform. 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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Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

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place for every integration

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

Common questions about Typeform MCP in OpenAI Agents SDK

Use the `get_form_details` tool. This gives you all the necessary information, including a breakdown of every question asked in that specific Typeform.
You just call `list_workspaces`. It provides an inventory of all the organizational containers for your Typeforms, helping you scope your agent's actions.
Yes. The `list_responses` tool lets you pull all submitted data. You can narrow this down by setting a 'since' date, so your agent only processes recent submissions.
The `list_design_themes` tool handles that. It pulls a list of all the design options you can use when building or updating your forms.
This server touches form submission responses, which include user-provided answers. The `list_responses` tool handles the retrieval of this sensitive completion data.

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