How to Use the bluebarry.ai MCP in OpenAI Agents SDK

Q: Can bluebarry.ai handle WhatsApp alerts in OpenAI Agents SDK?

The sendwhatsapp tool is ready for use as soon as you connect. Just define the recipient and payload within your agent's task flow.

Connect bluebarry.ai to your OpenAI Agents SDK production pipeline for instant WhatsApp messaging and YouTube video analysis.

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Connect bluebarry.ai MCP to OpenAI Agents SDK

Create your Vinkius account to connect bluebarry.ai 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 bluebarry.ai with OpenAI Agents SDK

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Watch and parse YouTube content

Your agent uses `analyze_youtube` to scrape video content directly into your context window. It skips the manual transcription steps. You'll get structured summaries that your OpenAI Agents SDK environment can process for immediate feedback.

Manage your automation and agent fleet

Call `list_agents` and `get_agent` to track your active bot roster within the SDK. You'll know exactly what each instance is doing. Use `get_automation_status` alongside `list_automations` to monitor your background tasks. This MCP Server gives your code total visibility into the backend.

Trigger messages from your agent

Invoke `send_whatsapp` directly from your agent logic to push updates to customers. It handles the delivery without leaving your Python codebase. Your agent confirms the message status in real-time. This keeps your communication loop tight and reliable.

Setup guide

Set up bluebarry.ai 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 bluebarry.ai tools at runtime.
3

Create your Agent

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

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate bluebarry.ai 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="bluebarry.ai Agent",
            instructions="You have access to bluebarry.ai 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 bluebarry.ai MCP in OpenAI Agents SDK

Install the required packages and define your connection using the MCPServerStreamableHttp class. Pass your instance into the Agent constructor and let the SDK handle the discovery.

Yes, set cacheToolsList=True in your configuration. This stops the agent from re-fetching tool definitions on every single turn.

The `send_whatsapp` tool is ready for use as soon as you connect. Just define the recipient and payload within your agent's task flow.

Calls are handled via HTTP, meaning performance depends on your network. The server is built for quick response times during agent execution.

Your customer phone numbers and message content never touch our logs. We use transient memory to route requests, ensuring your sensitive communication logs remain private.

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