Can I trigger a data extraction for a specific URL?

Yes! Use the `run_robot` tool with the Robot ID and the target URL (`origin_url`). Your agent will create a new task in Browse AI to extract the data instantly.

How do I retrieve the data once a robot finishes its task?

Simply ask the agent to `get_task` and provide the Task ID. If the status is 'successful', it will return the JSON structure containing all the captured data fields.

Can I list all the robots I have trained in my account?

Yes. Use the `list_robots` tool. It will retrieve all the approved robots currently available in your Browse AI dashboard, including their names and unique IDs.

Browse AI MCP Server for OpenAI Agents SDK 10 tools — connect in under 2 minutes

Name: Browse AI
Availability: InStock
Author: Vinkius

openai.github.io/openai-agents-python/mcp

Built by Vinkius GDPR 10 Tools SDK

The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Browse AI through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MCPServerStreamableHttp(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as mcp_server:

        agent = Agent(
            name="Browse AI Assistant",
            instructions=(
                "You help users interact with Browse AI. "
                "You have access to 10 tools."
            ),
            mcp_servers=[mcp_server],
        )

        result = await Runner.run(
            agent, "List all available tools from Browse AI"
        )
        print(result.final_output)

asyncio.run(main())

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DLPData protection

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Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Browse AI MCP Server

Connect your Browse AI account to any AI agent and orchestrate your web scraping, data extraction, and website monitoring workflows through natural conversation.

The OpenAI Agents SDK auto-discovers all 10 tools from Browse AI through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries Browse AI, another analyzes results, and a third generates reports, all orchestrated through Vinkius.

What you can do

Robot Oversight — List all your approved robots and retrieve detailed metadata for each scraper.
Task Execution — Trigger robot runs (tasks) on specific URLs and monitor their progress in real-time.
Data Retrieval — Retrieve structured data captured by your robots directly into your workspace.
Website Monitoring — List and create monitor schedules to track changes on any website automatically.
Bulk Operations — Manage and inspect bulk runs to extract data from multiple sources at once.
System Status — Check the health and queue status of the Browse AI infrastructure.

The Browse AI MCP Server exposes 10 tools through the Vinkius. Connect it to OpenAI Agents SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Browse AI to OpenAI Agents SDK via MCP

Follow these steps to integrate the Browse AI MCP Server with OpenAI Agents SDK.

Install the SDK

Run pip install openai-agents in your Python environment

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Run the script

Save the code above and run it: python agent.py

Explore tools

The agent will automatically discover 10 tools from Browse AI

Why Use OpenAI Agents SDK with the Browse AI MCP Server

OpenAI Agents SDK provides unique advantages when paired with Browse AI through the Model Context Protocol.

Native MCP integration via `MCPServerSse`, pass the URL and the SDK auto-discovers all tools with full type safety

Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure

Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate

First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output

Browse AI + OpenAI Agents SDK Use Cases

Practical scenarios where OpenAI Agents SDK combined with the Browse AI MCP Server delivers measurable value.

Automated workflows: build agents that query Browse AI, process the data, and trigger follow-up actions autonomously

Multi-agent orchestration: create specialist agents. one queries Browse AI, another analyzes results, a third generates reports

Data enrichment pipelines: stream data through Browse AI tools and transform it with OpenAI models in a single async loop

Customer support bots: agents query Browse AI to resolve tickets, look up records, and update statuses without human intervention

Browse AI MCP Tools for OpenAI Agents SDK (10)

These 10 tools become available when you connect Browse AI to OpenAI Agents SDK via MCP:

create_monitor

Create a new monitor schedule for a robot

get_bulk_run

Get details of a specific bulk run

get_robot

Get details of a specific robot

get_system_status

Check Browse AI system and queue status

get_task

Get status and extracted data for a task

list_bulk_runs

List all bulk runs for a robot

list_monitors

List all monitors for a specific robot

list_robots

List all approved robots

list_tasks

List all tasks for a specific robot

run_robot

Run a robot to extract data (creates a task)

Example Prompts for Browse AI in OpenAI Agents SDK

Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Browse AI immediately.

"List all my approved web scraping robots."

"Run robot rob_123 on https://example.com/product."

"Retrieve the data from task task_99283."

Troubleshooting Browse AI MCP Server with OpenAI Agents SDK

Common issues when connecting Browse AI to OpenAI Agents SDK through the Vinkius, and how to resolve them.

MCPServerStreamableHttp not found

Ensure you have the latest version: pip install --upgrade openai-agents

Agent not calling tools

Make sure your prompt explicitly references the task the tools can help with.

Browse AI + OpenAI Agents SDK FAQ

Common questions about integrating Browse AI MCP Server with OpenAI Agents SDK.

How does the OpenAI Agents SDK connect to MCP?

Use MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.