How to Use the Habitify MCP in OpenAI Agents SDK

Q: How do I connect Habitify to my OpenAI Agents SDK project?

You initialize the connection using MCPServerStreamableHttp within your agent constructor. The SDK handles discovery automatically once you pass the server reference to your agent.

Q: Can OpenAI Agents SDK manage multiple Habitify areas?

Yes, use listareas to fetch your categories. The agent can then filter specific tasks using listhabits based on the area ID.

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Connect Habitify MCP to OpenAI Agents SDK

Create your Vinkius account to connect Habitify 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 Habitify with OpenAI Agents SDK

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Automated habit logging for OpenAI Agents SDK

Stop manual entry. Your agent uses `add_habit_log` to record daily progress directly from conversation context. This keeps your data current without forcing you to switch tabs or open the app.

Real-time state tracking in your agent

Call `list_habits` to pull your current routine into the agent's memory. It understands exactly what you need to do next. You avoid stale information because the agent queries your live account status every time it runs.

Deep analytical insights via MCP

Use `get_habit_stats` to generate performance reports inside your agent's workflow. It calculates trends based on your actual history. Feeding this data into your agent allows for personalized coaching based on verified completion rates.

Setup guide

Set up Habitify 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 Habitify tools at runtime.
3

Create your Agent

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

Run the agent

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

asyncio.run(main())

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Common questions about Habitify MCP in OpenAI Agents SDK

You initialize the connection using `MCPServerStreamableHttp` within your agent constructor. The SDK handles discovery automatically once you pass the server reference to your agent.

Yes, use `list_areas` to fetch your categories. The agent can then filter specific tasks using `list_habits` based on the area ID.

It does. Since the OpenAI Agents SDK is built for async, you use an async context manager to wrap the server connection and ensure non-blocking execution.

You should implement a confirmation step. Have the agent call `get_habit` first to verify the ID, then perform the log action.

The server uses your unique endpoint token to handle requests. Your habit logs and personal stats never leave the secure tunnel between your agent and the server.

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