Browse AI MCP Server for OpenAI Agents SDK 10 tools — connect in under 2 minutes
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.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
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())
* 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 take full control of your no-code web scraping operations 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 Discovery — List all your trained extraction and monitoring robots along with their configuration details
- Execute Scrapes — Trigger specific robots to run tasks on target URLs without lifting a finger
- Data Retrieval — Instantly download the final extracted JSON data from any successfully completed task
- Bulk Operations — Initiate multi-URL concurrent extractions and download the unified bulk datasets
- Monitor Sync — Check the status of your active web change monitors
- Quota Management — Retrieve your current API credits usage and monthly plan limits
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:
download_bulk_data
Returns a JSON array where each element contains the capturedData from one task. Download all extracted results from a completed Browse AI bulk run
get_bulk_task
Get bulk task execution status from Browse AI
get_robot
Get detailed configuration of a specific Browse AI robot
get_task
Check the status of a specific Browse AI extraction task
get_task_data
Only meaningful when the task status is "successful". Fields match the column names configured in the Browse AI robot builder hitting internal task references. Retrieve the final extracted JSON data from a successful Browse AI task
list_credits
Check Browse AI quota limits and credit usage
list_monitors
Monitors run on scheduled intervals to detect changes on target web pages and trigger notifications or data captures automatically via `/monitors`. List all active Browse AI web monitoring robots
list_robots
Each robot represents a no-code AI scraping workflow targeting a specific website or data pattern via `GET /robots`. List all Browse AI extraction and monitoring robots
run_bulk_task
Each set typically contains a different "originUrl". All extractions run concurrently on Browse AI infrastructure. Run a Browse AI robot in bulk mode across multiple URLs
run_robot
Pass a JSON string of input parameters (typically including "originUrl" for the target page and any variable fields the robot expects). Returns a taskId. Trigger a Browse AI robot to extract data from a target URL
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 robots. Which ones are built for monitoring?"
"Run my HackerNews Scraper robot on the main page."
"Retrieve the JSON data for task t-78ab31."
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
pip install --upgrade openai-agentsAgent not calling tools
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?
MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.Can I use multiple MCP servers in one agent?
MCPServerSse instances to the agent constructor. The agent can use tools from all connected servers within a single run.Does the SDK support streaming responses?
Connect Browse AI with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Browse AI to OpenAI Agents SDK
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.