How to Use the BugBug MCP in OpenAI Agents SDK

Q: Can OpenAI Agents SDK see my BugBug test history?

Absolutely. Use the listtestruns tool to pull recent execution data directly into your agent's context window.

Q: Is the connection between BugBug and the SDK stable?

Setting cacheToolsList=True ensures the tool definitions stay cached. This makes the interaction between the two much faster during high-volume agent tasks.

Trigger BugBug test runs directly from your OpenAI Agents SDK production pipeline.

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Connect BugBug MCP to OpenAI Agents SDK

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

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Automate test triggers in OpenAI Agents SDK

Trigger specific test suites or individual checks using `run_suite` and `run_test` directly from your agent logic. You define the conditions, and the agent executes the tests as part of your safety guardrails. Your agent checks the status of execution with `get_test_run` or `get_suite_run` to decide on the next step. This keeps your production environment clean without manual intervention.

Observe BugBug states inside OpenAI Agents SDK

Query your current test inventory using `list_tests` and `list_suites` to understand what coverage exists. The agent pulls this data to map out which areas of your web app need validation before deployment. You gain visibility into project structures by calling `list_projects`. It provides the exact context your agent needs to navigate complex web testing workflows.

Manage infrastructure for OpenAI Agents SDK

Fetch current network configurations with `get_ips` to keep your firewall rules updated for your test runs. This ensures the MCP server maintains a clear line to your web interface. Check your history using `list_test_runs` or `list_suite_runs` to see if regressions are creeping back in. You get the raw data needed to audit agent performance over time.

Setup guide

Set up BugBug 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 BugBug tools at runtime.
3

Create your Agent

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

Run the agent

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

Initialize your agent with the server URL and the tools are auto-discovered. Call the `run_test` function within your agent loop to trigger specific checks.

Yes, it integrates natively. The agent validates each action before execution, ensuring that test triggers adhere to your defined safety constraints.

Absolutely. Use the `list_test_runs` tool to pull recent execution data directly into your agent's context window.

Setting `cacheToolsList=True` ensures the tool definitions stay cached. This makes the interaction between the two much faster during high-volume agent tasks.

The server only touches your test run metadata and IP allowlists. No user-facing web content is processed or stored by our infrastructure.

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