How to Use the Typeform MCP in OpenAI Agents SDK
Build production agents for Typeform: Connect your OpenAI Agents SDK to structured form data.
Works with every AI agent you already use
…and any MCP-compatible client
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.
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.
Set up Typeform MCP in OpenAI Agents SDK
Prerequisites
- Python 3.10+ installed
-
openai-agentspackage (pip install openai-agents) - Active Vinkius subscription with a valid endpoint token
- 1
Install the SDK
Run
pip install openai-agentsto install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed. - 2
Connect via SSE transport
Use
MCPServerSsewith 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
Create your Agent
Pass the MCP to
Agent(mcp_servers=[server]). The agent receives Typeform tools as native definitions — JSON schemas resolve automatically. - 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.
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.
Why Choose Vinkius
Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.
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 Typeform MCP in OpenAI Agents SDK
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