How to Use the Google Lighthouse SEO Auditor MCP in OpenAI Agents SDK

Q: How do I connect the Google Lighthouse SEO Auditor to my OpenAI Agents SDK pipeline?

Install openai-agents first. Then, initialize MCPServerStreamableHttp with your Vinkius endpoint. Pass this server object into your agent's constructor inside an async context manager, and the agent will automatically discover the runlighthouseaudit tool.

Q: Can OpenAI Agents SDK automatically fix the SEO errors found by the Google Lighthouse SEO Auditor?

Yes, if you configure your agent to write code. The runlighthouseaudit tool returns specific failed audits, like bloated JS bundles, which your agent can analyze to generate precise code patches.

Run real-time PageSpeed audits inside OpenAI Agents SDK to fix performance issues before they hit search rankings.

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Connect Google Lighthouse SEO Auditor MCP to OpenAI Agents SDK

Create your Vinkius account to connect Google Lighthouse SEO Auditor 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 Google Lighthouse SEO Auditor with OpenAI Agents SDK

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Run audits directly from your OpenAI Agents SDK pipeline

Your OpenAI agent can now run a complete performance check on any live website. By calling the `run_lighthouse_audit` tool, the agent grabs actual PageSpeed scores and lists exact issues like unoptimized images or render-blocking scripts. This lets your system flag slow pages without leaving the terminal. Setting this up takes seconds. You register the MCP Server in your Python backend, and the agent auto-discovers the tool. It gets direct access to raw performance data, skipping the need for manual browser testing.

Safe, guarded execution for production web teams

Production systems require guardrails. When your agent triggers `run_lighthouse_audit`, the OpenAI Agents SDK validates the tool call before hitting the external endpoint. You get complete tracing on your dashboard, so you know exactly which URLs your agent analyzed and how much budget it spent. If an agent tries to audit an invalid domain, your guardrails catch it instantly. The integration handles rate limits and connection pooling behind the scenes, keeping your production pipelines stable.

Handoffs between SEO and dev agent specialists

Complex web projects need different agents for different tasks. One agent can run `run_lighthouse_audit` to find slow assets, then hand off the raw audit data to a developer agent. That developer agent then writes the exact CSS or HTML fixes to resolve the issue. This multi-agent coordination happens natively within the OpenAI framework. Because the MCP server returns structured JSON, your agents pass the data back and forth without losing context or corrupting the payload.

Setup guide

Set up Google Lighthouse SEO Auditor 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 Google Lighthouse SEO Auditor tools at runtime.
3

Create your Agent

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

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Google Lighthouse SEO Auditor 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="Google Lighthouse SEO Auditor Agent",
            instructions="You have access to Google Lighthouse SEO Auditor tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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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 Google PageSpeed. 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 Google Lighthouse SEO Auditor MCP in OpenAI Agents SDK

Install `openai-agents` first. Then, initialize `MCPServerStreamableHttp` with your Vinkius endpoint. Pass this server object into your agent's constructor inside an async context manager, and the agent will automatically discover the `run_lighthouse_audit` tool.

Yes, if you configure your agent to write code. The `run_lighthouse_audit` tool returns specific failed audits, like bloated JS bundles, which your agent can analyze to generate precise code patches.

Vinkius hosts the MCP server on a secure, scaled infrastructure. For high-volume production pipelines, you should set `cacheToolsList=True` in your Python setup to avoid redundant schema discovery calls.

No. The server executes audits via the Google PageSpeed Insights API. Your agent gets raw JSON results instantly without the overhead of running a headless browser in your production container.

Vinkius runs the server in an ephemeral sandbox. The target URLs you audit and the resulting PageSpeed JSON reports are never stored on our disks, keeping your proprietary staging links completely confidential.

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