How to Use the BrowserStack MCP in AutoGen

Q: How do AutoGen agents share BrowserStack tool outputs with each other?

One agent executes a tool like getsession and posts the JSON result to the group chat. All other agents in the AutoGen group read this output to make their next decisions.

Q: Does this setup support execution across multiple testing projects?

Yes, agents use listprojects to discover all active projects in your account. They switch between projects dynamically based on the conversation context.

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Setup BrowserStack with AutoGen

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Consensus-driven test triage with AutoGen MCP Server

This MCP Server allows multiple AutoGen agents to collaborate on test suite failures. A triage agent calls `get_build` to inspect failed runs, while a developer agent analyzes the logs. They debate the root cause of the failure in a shared conversation thread. This collaborative analysis leads to more accurate bug identification before human developers intervene.

Automated pipeline cleanup via agent debate

When test runs accumulate, a budget agent uses `list_projects` and `list_builds` to find old or redundant data. It proposes deletions to a security agent in the conversation. Only after both agents agree on the safety parameters does the executor agent call `delete_build` or `delete_session`. This prevents accidental deletion of critical historical data.

Resource-aware suite execution planning

Before launching a test run, an execution agent checks capacity using `get_plan`. It presents the current parallel session usage to the coordinator agent. If resources are constrained, the coordinator agent adjusts the execution strategy. This negotiation ensures your team never hits concurrency limits or queues critical builds.

Setup guide

Set up BrowserStack MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes BrowserStack tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="BrowserStack_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent BrowserStack data")
print(result.messages[-1].content)

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Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="BrowserStack_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent BrowserStack data")
    print(result.messages[-1].content)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by BrowserStack. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about BrowserStack MCP in AutoGen

One agent executes a tool like `get_session` and posts the JSON result to the group chat. All other agents in the AutoGen group read this output to make their next decisions.

You configure the safety parameters of your agents. You can require a human-in-the-loop approval step before the agent executes `delete_session` or `delete_build`.

You use the autogen-ext MCP adapter to fetch the tools from the server. Pass the resulting tool list directly into your AssistantAgent constructor.

Yes, agents use `list_projects` to discover all active projects in your account. They switch between projects dynamically based on the conversation context.

Your API credentials remain locked in an isolated V8 sandbox on the host platform. The AutoGen agents only interact with the exposed tools, meaning raw credentials never enter the agent conversation logs or LLM prompts.

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