How to Use the BrowserStack MCP in OpenAI Agents SDK

Q: Can my OpenAI Agents SDK assistant delete active test runs on BrowserStack?

Yes, your agent can call deletebuild or deletesession if you expose those tools. You can use the SDK's built-in guardrails to restrict these destructive actions.

Q: How does the BrowserStack MCP Server handle session limits in OpenAI Agents SDK?

The agent queries getplan to check concurrency limits before spinning up new test runs. This lets your Python agent manage execution queues without hitting API rate limits.

Deploy self-healing test automation pipelines with OpenAI Agents SDK to manage and debug BrowserStack builds automatically.

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Connect BrowserStack MCP to OpenAI Agents SDK

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

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Automated Build Management in OpenAI Agents SDK

Your OpenAI agent uses `list_builds` to monitor active BrowserStack runs and target specific test execution pipelines. If a run hangs or fails, the agent calls `delete_build` directly through the MCP Server to clean up resources. Because you are deploying to production with the OpenAI Agents SDK, you can set up guardrails that intercept these destructive actions. Before the agent executes `delete_build`, your safety layer prompts for human approval or validates the build ID.

Deep Session Debugging and Log Analysis

The agent pulls raw text logs using `get_session_logs` and inspects the execution environment details with `get_session`. This gives your system the exact error traceback and the video URL of the failing test run. By feeding this data into your OpenAI agent's reasoning loop, it can diagnose why a test failed on a specific OS version. It matches the console output against your codebase to suggest immediate code fixes.

Dynamic Concurrency and Browser Mapping

Your agent calls `get_plan` to inspect parallel session limits and `list_browsers` to fetch supported OS configurations using this MCP Server. This prevents your automated testing pipeline from hitting execution limits or using unsupported desired capabilities. Instead of hardcoding test matrices, the agent adjusts your test runner's thread count dynamically based on current queue usage. It matches your target browser list against what BrowserStack currently supports to avoid configuration errors.

Setup guide

Set up BrowserStack 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 BrowserStack tools at runtime.
3

Create your Agent

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

Run the agent

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

Use the MCPServerStreamableHttp class to connect the Vinkius endpoint to your agent constructor. Pass it as a server inside your mcp_servers list, and the SDK will auto-discover all ten automation tools.

Yes, your agent can call delete_build or delete_session if you expose those tools. You can use the SDK's built-in guardrails to restrict these destructive actions.

The agent queries get_plan to check concurrency limits before spinning up new test runs. This lets your Python agent manage execution queues without hitting API rate limits.

Set cacheToolsList to true in your connection parameters. This prevents the agent from fetching the tool list on every single turn, reducing latency.

This server exposes build logs, session metadata, video URLs, and project structures retrieved by tools like get_session_logs. All communication flows through Vinkius's secure, ephemeral sandbox, meaning your raw test credentials and source code never persist outside your direct execution context.

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