How to Use the Appcues MCP in OpenAI Agents SDK

Q: How do I connect Appcues to OpenAI Agents SDK?

Install openai-agents via pip. Create an MCPServerStreamableHttp instance pointing to your Vinkius endpoint. Pass it to your Agent constructor in the mcpservers list.

Q: Can OpenAI Agents SDK publish Appcues flows automatically?

Yes. Your agent can call publishflow to push draft experiences live. You can set up safety constraints to require human approval before this specific tool executes.

Q: Does the Appcues MCP Server support event tracking?

It does. The trackuseractivity tool accepts JSON strings for events and profile updates. Your agent formats the payload and sends it straight to the Appcues API.

Q: How do I check active user segments using Appcues and OpenAI Agents SDK?

Have your agent run listsegments to get the full list. If you need the exact rules for one group, it calls getsegment with the specific ID.

Connect Appcues to your OpenAI Agents SDK system to automatically track user events and manage onboarding flows in production.

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Connect Appcues MCP to OpenAI Agents SDK

Create your Vinkius account to connect Appcues 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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Setup Appcues with OpenAI Agents SDK

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Control Appcues flows with OpenAI Agents SDK

Your multi-agent setup uses `list_flows` to handle product onboarding without human intervention. Instead of manually clicking through the Appcues dashboard, your agent checks what is currently running. It then decides if a specific experience needs an update based on user telemetry. When a new feature drops, a specialized release agent triggers `publish_flow` to push the new tooltip live. If metrics tank, a fallback agent hits `unpublish_flow` immediately. The OpenAI dashboard traces every single tool execution, so you know exactly which agent touched your live user experiences.

Track user activity via MCP Server

Production systems execute `track_user_activity` via this MCP Server to log custom events and update profile attributes in real time. You define the exact JSON schemas for profile updates, and the agent follows them. Before pushing an event, your agent verifies the current state with `get_user_profile`. This prevents duplicate data entries and keeps your analytics clean. Handoffs between a data-gathering agent and an event-tracking agent happen automatically within the SDK framework.

Read segments and mobile experiences

Agents pull current definitions using `list_segments` to understand exactly who sees which in-app message. They drill down into specific audience rules with `get_segment`. This lets your system read the exact logic behind your campaigns. You also get full visibility into other growth channels. The agent runs `list_checklists` to audit onboarding steps or `list_mobile_experiences` for iOS and Android campaigns. Every read operation through the MCP Server is validated by OpenAI guardrails before the agent decides what to do next.

Setup guide

Set up Appcues 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

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

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 Appcues tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives Appcues tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Appcues 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="Appcues Agent",
            instructions="You have access to Appcues tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Appcues. 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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Common questions about Appcues MCP in OpenAI Agents SDK

Install `openai-agents` via pip. Create an `MCPServerStreamableHttp` instance pointing to your Vinkius endpoint. Pass it to your Agent constructor in the `mcp_servers` list.

Yes. Your agent can call `publish_flow` to push draft experiences live. You can set up safety constraints to require human approval before this specific tool executes.

It does. The `track_user_activity` tool accepts JSON strings for events and profile updates. Your agent formats the payload and sends it straight to the Appcues API.

Have your agent run `list_segments` to get the full list. If you need the exact rules for one group, it calls `get_segment` with the specific ID.

Vinkius runs this server inside an ephemeral V8 Isolate Sandbox. When your agent pulls a payload via `get_user_profile`, the data passes through a zero-trust tunnel. No user telemetry or segment rules are ever stored on our infrastructure.

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