# How to integrate GTmetrix MCP with Mastra AI

```json
{
  "title": "How to integrate GTmetrix MCP with Mastra AI",
  "toolkit": "GTmetrix",
  "toolkit_slug": "gtmetrix",
  "framework": "Mastra AI",
  "framework_slug": "mastra-ai",
  "url": "https://composio.dev/toolkits/gtmetrix/framework/mastra-ai",
  "markdown_url": "https://composio.dev/toolkits/gtmetrix/framework/mastra-ai.md",
  "updated_at": "2026-03-29T06:36:47.678Z"
}
```

## Introduction

This guide walks you through connecting GTmetrix to Mastra AI using the Composio tool router. By the end, you'll have a working GTmetrix agent that can run a performance test on your homepage, check latest gtmetrix report for example.com, list top optimization recommendations for your site through natural language commands.
This guide will help you understand how to give your Mastra AI agent real control over a GTmetrix account through Composio's GTmetrix MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate GTmetrix with

- [OpenAI Agents SDK](https://composio.dev/toolkits/gtmetrix/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/gtmetrix/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/gtmetrix/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/gtmetrix/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/gtmetrix/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/gtmetrix/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/gtmetrix/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/gtmetrix/framework/cli)
- [Google ADK](https://composio.dev/toolkits/gtmetrix/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/gtmetrix/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/gtmetrix/framework/ai-sdk)
- [LlamaIndex](https://composio.dev/toolkits/gtmetrix/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/gtmetrix/framework/crew-ai)

## TL;DR

Here's what you'll learn:
- Set up your environment so Mastra, OpenAI, and Composio work together
- Create a Tool Router session in Composio that exposes GTmetrix tools
- Connect Mastra's MCP client to the Composio generated MCP URL
- Fetch GTmetrix tool definitions and attach them as a toolset
- Build a Mastra agent that can reason, call tools, and return structured results
- Run an interactive CLI where you can chat with your GTmetrix agent

## What is Mastra AI?

Mastra AI is a TypeScript framework for building AI agents with tool support. It provides a clean API for creating agents that can use external services through MCP.
Key features include:
- MCP Client: Built-in support for Model Context Protocol servers
- Toolsets: Organize tools into logical groups
- Step Callbacks: Monitor and debug agent execution
- OpenAI Integration: Works with OpenAI models via @ai-sdk/openai

## What is the GTmetrix MCP server, and what's possible with it?

The GTmetrix MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your GTmetrix account. It provides structured and secure access so your agent can perform GTmetrix operations on your behalf.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `GTMETRIX_DELETE_PAGE` | Delete Page | Tool to delete a specific page in GTmetrix. Use when you need to permanently remove a page resource. |
| `GTMETRIX_DELETE_REPORT` | Delete Report | Tool to delete a GTmetrix report. Use when you need to remove an existing performance report from GTmetrix. |
| `GTMETRIX_GET_BROWSERS` | Get Browsers | Tool to retrieve the list of available browsers for GTmetrix performance tests. Use when you need to see which browsers are available and their testing capabilities. |
| `GTMETRIX_GET_LOCATION` | Get Location Details | Tool to retrieve location details from GTmetrix. Use when you need to get information about a specific GTmetrix test location including name, region, browser support, IP addresses, and access permissions. |
| `GTMETRIX_GET_LOCATIONS` | Get Locations | Tool to retrieve the list of available GTmetrix test locations. Use when you need to see which locations are available for testing and their details including supported browsers and access status. |
| `GTMETRIX_GET_PAGE_DETAILS` | Get Page Details | Tool to retrieve page details from the user's GTmetrix account. Use when you need to get comprehensive page information including URL, testing configuration, and monitoring frequency. |
| `GTMETRIX_GET_PAGE_REPORTS` | Get Page Reports | Tool to retrieve the report list associated with a monitored page in GTmetrix. Use when you need to access historical performance data for a specific page. Supports pagination, sorting, and filtering. |
| `GTMETRIX_GET_PAGES` | Get Pages | Tool to retrieve the page list from your GTmetrix account. Returns a paginated collection of monitored pages with their configurations and latest report information. Use when you need to view all monitored pages, check page configurations, or access latest report data. |
| `GTMETRIX_GET_REPORT` | Get Report | Tool to retrieve a GTmetrix test report by its identifier. Use when you need to get comprehensive performance metrics, timing data, and links to resources for a specific report. |
| `GTMETRIX_GET_SIMULATED_DEVICE` | Get Simulated Device | Tool to retrieve simulated device details. Use when you need information about a specific simulated device including its name, category, manufacturer, user agent, screen dimensions, and pixel ratio. |
| `GTMETRIX_GET_SIMULATED_DEVICES` | Get Simulated Devices | Tool to retrieve the list of simulated devices available in GTmetrix. Use when you need to see available device profiles for testing. |
| `GTMETRIX_GET_API_ACCOUNT_STATUS` | Get API Account Status | Tool to retrieve the current API account state and remaining credits. Use to check available API credits, refill schedule, and account features. |
| `GTMETRIX_GET_TEST_DETAILS` | Get Test Details | Tool to retrieve test details for a specific GTMetrix test. Use when you need to check the status, configuration, or results of a previously initiated test. |
| `GTMETRIX_GET_TESTS` | Get Tests | Tool to retrieve the test list from your GTmetrix account with pagination and filtering support. Use when you need to view tests with their state, timestamps, and configuration details. |
| `GTMETRIX_RETEST_REPORT` | Retest Report | Tool to initiate a retest of a completed GTmetrix report with same parameters. Use when you need to rerun a test using the exact same analysis parameters as the original test. |
| `GTMETRIX_START_TEST` | Start Test | Tool to start a new GTmetrix test for a specified URL. Use when you need to analyze website performance with configurable options like location, browser, and throttling. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The GTmetrix MCP server is an implementation of the Model Context Protocol that connects your AI agent to GTmetrix. It provides structured and secure access so your agent can perform GTmetrix operations on your behalf through a secure, permission-based interface.
With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster.

## Step-by-step Guide

### 1. Prerequisites

Before starting, make sure you have:
- Node.js 18 or higher
- A Composio account with an active API key
- An OpenAI API key
- Basic familiarity with TypeScript

### 1. Getting API Keys for OpenAI and Composio

OpenAI API Key
- Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) and create an API key.
- You need credits or a connected billing setup to use the models.
- Store the key somewhere safe.
Composio API Key
- Log in to the [Composio dashboard](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs).
- Go to Settings and copy your API key.
- This key lets your Mastra agent talk to Composio and reach GTmetrix through MCP.

### 2. Install dependencies

Install the required packages.
What's happening:
- @composio/core is the Composio SDK for creating MCP sessions
- @mastra/core provides the Agent class
- @mastra/mcp is Mastra's MCP client
- @ai-sdk/openai is the model wrapper for OpenAI
- dotenv loads environment variables from .env
```bash
npm install @composio/core @mastra/core @mastra/mcp @ai-sdk/openai dotenv
```

### 3. Set up environment variables

Create a .env file in your project root.
What's happening:
- COMPOSIO_API_KEY authenticates your requests to Composio
- COMPOSIO_USER_ID tells Composio which user this session belongs to
- OPENAI_API_KEY lets the Mastra agent call OpenAI models
```bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here
```

### 4. Import libraries and validate environment

What's happening:
- dotenv/config auto loads your .env so process.env.* is available
- openai gives you a Mastra compatible model wrapper
- Agent is the Mastra agent that will call tools and produce answers
- MCPClient connects Mastra to your Composio MCP server
- Composio is used to create a Tool Router session
```typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Agent } from "@mastra/core/agent";
import { MCPClient } from "@mastra/mcp";
import { Composio } from "@composio/core";
import * as readline from "readline";

import type { AiMessageType } from "@mastra/core/agent";

const openaiAPIKey = process.env.OPENAI_API_KEY;
const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!openaiAPIKey) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({
  apiKey: composioAPIKey as string,
});
```

### 5. Create a Tool Router session for GTmetrix

What's happening:
- create spins up a short-lived MCP HTTP endpoint for this user
- The toolkits array contains "gtmetrix" for GTmetrix access
- session.mcp.url is the MCP URL that Mastra's MCPClient will connect to
```typescript
async function main() {
  const session = await composio.create(
    composioUserID as string,
    {
      toolkits: ["gtmetrix"],
    },
  );

  const composioMCPUrl = session.mcp.url;
  console.log("GTmetrix MCP URL:", composioMCPUrl);
```

### 6. Configure Mastra MCP client and fetch tools

What's happening:
- MCPClient takes an id for this client and a list of MCP servers
- The headers property includes the x-api-key for authentication
- getTools fetches the tool definitions exposed by the GTmetrix toolkit
```typescript
const mcpClient = new MCPClient({
    id: composioUserID as string,
    servers: {
      nasdaq: {
        url: new URL(composioMCPUrl),
        requestInit: {
          headers: session.mcp.headers,
        },
      },
    },
    timeout: 30_000,
  });

console.log("Fetching MCP tools from Composio...");
const composioTools = await mcpClient.getTools();
console.log("Number of tools:", Object.keys(composioTools).length);
```

### 7. Create the Mastra agent

What's happening:
- Agent is the core Mastra agent
- name is just an identifier for logging and debugging
- instructions guide the agent to use tools instead of only answering in natural language
- model uses openai("gpt-5") to configure the underlying LLM
```typescript
const agent = new Agent({
    name: "gtmetrix-mastra-agent",
    instructions: "You are an AI agent with GTmetrix tools via Composio.",
    model: "openai/gpt-5",
  });
```

### 8. Set up interactive chat interface

What's happening:
- messages keeps the full conversation history in Mastra's expected format
- agent.generate runs the agent with conversation history and GTmetrix toolsets
- maxSteps limits how many tool calls the agent can take in a single run
- onStepFinish is a hook that prints intermediate steps for debugging
```typescript
let messages: AiMessageType[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end.\n");

const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
  prompt: "> ",
});

rl.prompt();

rl.on("line", async (userInput: string) => {
  const trimmedInput = userInput.trim();

  if (["exit", "quit", "bye"].includes(trimmedInput.toLowerCase())) {
    console.log("\nGoodbye!");
    rl.close();
    process.exit(0);
  }

  if (!trimmedInput) {
    rl.prompt();
    return;
  }

  messages.push({
    id: crypto.randomUUID(),
    role: "user",
    content: trimmedInput,
  });

  console.log("\nAgent is thinking...\n");

  try {
    const response = await agent.generate(messages, {
      toolsets: {
        gtmetrix: composioTools,
      },
      maxSteps: 8,
    });

    const { text } = response;

    if (text && text.trim().length > 0) {
      console.log(`Agent: ${text}\n`);
        messages.push({
          id: crypto.randomUUID(),
          role: "assistant",
          content: text,
        });
      }
    } catch (error) {
      console.error("\nError:", error);
    }

    rl.prompt();
  });

  rl.on("close", async () => {
    console.log("\nSession ended.");
    await mcpClient.disconnect();
    process.exit(0);
  });
}

main().catch((err) => {
  console.error("Fatal error:", err);
  process.exit(1);
});
```

## Complete Code

```typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Agent } from "@mastra/core/agent";
import { MCPClient } from "@mastra/mcp";
import { Composio } from "@composio/core";
import * as readline from "readline";

import type { AiMessageType } from "@mastra/core/agent";

const openaiAPIKey = process.env.OPENAI_API_KEY;
const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!openaiAPIKey) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({ apiKey: composioAPIKey as string });

async function main() {
  const session = await composio.create(composioUserID as string, {
    toolkits: ["gtmetrix"],
  });

  const composioMCPUrl = session.mcp.url;

  const mcpClient = new MCPClient({
    id: composioUserID as string,
    servers: {
      gtmetrix: {
        url: new URL(composioMCPUrl),
        requestInit: {
          headers: session.mcp.headers,
        },
      },
    },
    timeout: 30_000,
  });

  const composioTools = await mcpClient.getTools();

  const agent = new Agent({
    name: "gtmetrix-mastra-agent",
    instructions: "You are an AI agent with GTmetrix tools via Composio.",
    model: "openai/gpt-5",
  });

  let messages: AiMessageType[] = [];

  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: "> ",
  });

  rl.prompt();

  rl.on("line", async (input: string) => {
    const trimmed = input.trim();
    if (["exit", "quit"].includes(trimmed.toLowerCase())) {
      rl.close();
      return;
    }

    messages.push({ id: crypto.randomUUID(), role: "user", content: trimmed });

    const { text } = await agent.generate(messages, {
      toolsets: { gtmetrix: composioTools },
      maxSteps: 8,
    });

    if (text) {
      console.log(`Agent: ${text}\n`);
      messages.push({ id: crypto.randomUUID(), role: "assistant", content: text });
    }

    rl.prompt();
  });

  rl.on("close", async () => {
    await mcpClient.disconnect();
    process.exit(0);
  });
}

main();
```

## Conclusion

You've built a Mastra AI agent that can interact with GTmetrix through Composio's Tool Router.
You can extend this further by:
- Adding other toolkits like Gmail, Slack, or GitHub
- Building a web-based chat interface around this agent
- Using multiple MCP endpoints to enable cross-app workflows

## How to build GTmetrix MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/gtmetrix/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/gtmetrix/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/gtmetrix/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/gtmetrix/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/gtmetrix/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/gtmetrix/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/gtmetrix/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/gtmetrix/framework/cli)
- [Google ADK](https://composio.dev/toolkits/gtmetrix/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/gtmetrix/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/gtmetrix/framework/ai-sdk)
- [LlamaIndex](https://composio.dev/toolkits/gtmetrix/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/gtmetrix/framework/crew-ai)

## Related Toolkits

- [Google Sheets](https://composio.dev/toolkits/googlesheets) - Google Sheets is a cloud-based spreadsheet tool for real-time collaboration and data analysis. It lets teams work together from anywhere, updating information instantly.
- [Supabase](https://composio.dev/toolkits/supabase) - Supabase is an open-source backend platform offering scalable Postgres databases, authentication, storage, and real-time APIs. It lets developers build modern apps without managing infrastructure.
- [Notion](https://composio.dev/toolkits/notion) - Notion is a collaborative workspace for notes, docs, wikis, and tasks. It streamlines team knowledge, project tracking, and workflow customization in one place.
- [Airtable](https://composio.dev/toolkits/airtable) - Airtable combines the flexibility of spreadsheets with the power of a database for easy project and data management. Teams use Airtable to organize, track, and collaborate with custom views and automations.
- [Codeinterpreter](https://composio.dev/toolkits/codeinterpreter) - Codeinterpreter is a Python-based coding environment with built-in data analysis and visualization. It lets you instantly run scripts, plot results, and prototype solutions inside supported platforms.
- [Asana](https://composio.dev/toolkits/asana) - Asana is a collaborative work management platform for teams to organize and track projects. It streamlines teamwork, boosts productivity, and keeps everyone aligned on goals.
- [Google Tasks](https://composio.dev/toolkits/googletasks) - Google Tasks is a to-do list and task management tool integrated into Gmail and Google Calendar. It helps you organize, track, and complete tasks across your Google ecosystem.
- [Linear](https://composio.dev/toolkits/linear) - Linear is a modern issue tracking and project planning tool for fast-moving teams. It helps streamline workflows, organize projects, and boost productivity.
- [GitHub](https://composio.dev/toolkits/github) - GitHub is a code hosting platform for version control and collaborative software development. It streamlines project management, code review, and team workflows in one place.
- [Firecrawl](https://composio.dev/toolkits/firecrawl) - Firecrawl automates large-scale web crawling and data extraction. It helps organizations efficiently gather, index, and analyze content from online sources.
- [Tavily](https://composio.dev/toolkits/tavily) - Tavily offers powerful search and data retrieval from documents, databases, and the web. It helps teams locate and filter information instantly, saving hours on research.
- [Jira](https://composio.dev/toolkits/jira) - Jira is Atlassian’s platform for bug tracking, issue tracking, and agile project management. It helps teams organize work, prioritize tasks, and deliver projects efficiently.
- [Exa](https://composio.dev/toolkits/exa) - Exa is a data extraction and search platform for gathering and analyzing information from websites, APIs, or databases. It helps teams quickly surface insights and automate data-driven workflows.
- [Serpapi](https://composio.dev/toolkits/serpapi) - SerpApi is a real-time API for structured search engine results. It lets you automate SERP data collection, parsing, and analysis for SEO and research.
- [Clickup](https://composio.dev/toolkits/clickup) - ClickUp is an all-in-one productivity platform for managing tasks, docs, goals, and team collaboration. It streamlines project workflows so teams can work smarter and stay organized in one place.
- [Monday](https://composio.dev/toolkits/monday) - Monday.com is a customizable work management platform for project planning and collaboration. It helps teams organize tasks, automate workflows, and track progress in real time.
- [Peopledatalabs](https://composio.dev/toolkits/peopledatalabs) - Peopledatalabs delivers B2B data enrichment and identity resolution APIs. Supercharge your apps with accurate, up-to-date business and contact data.
- [Snowflake](https://composio.dev/toolkits/snowflake) - Snowflake is a cloud data warehouse built for elastic scaling, secure data sharing, and fast SQL analytics across major clouds.
- [Posthog](https://composio.dev/toolkits/posthog) - PostHog is an open-source analytics platform for tracking user interactions and product metrics. It helps teams refine features, analyze funnels, and reduce churn with actionable insights.
- [Ably](https://composio.dev/toolkits/ably) - Ably is a real-time messaging platform for live chat and data sync in modern apps. It offers global scale and rock-solid reliability for seamless, instant experiences.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and GTmetrix MCP?

With a standalone GTmetrix MCP server, the agents and LLMs can only access a fixed set of GTmetrix tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from GTmetrix and many other apps based on the task at hand, all through a single MCP endpoint.

### Can I use Tool Router MCP with Mastra AI?

Yes, you can. Mastra AI fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right GTmetrix tools.

### Can I manage the permissions and scopes for GTmetrix while using Tool Router?

Yes, absolutely. You can configure which GTmetrix scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

### How safe is my data with Composio Tool Router?

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your GTmetrix data and credentials are handled as safely as possible.

---
[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)
