GTmetrix MCP

Live

OAUTH 2.0

DEVELOPER TOOLS

Developer Tools

Connect to GTmetrix MCP to analyze web page performance, run speed tests, monitor Core Web Vitals, and get actionable optimization recommendations...

  • Acts as the user: Every tool call runs as the authorizing user. Access and audit trail stay intact.
  • Credentials stay vaulted: AES-256 encrypted, resolved at request time, never stored in LLM context.
  • Scoped before every call: Per-user permissions enforced automatically. 90-day audit trail included.
GTmetrix MCP
agent · Acme Q3
Run
Get Account Status in GTmetrix MCP
S
gtmetrixmcp_get_account_status
85ms
GTmetrix MCP agent
Returns the current gtmetrix account status including plan type, remaining api credits, next refill date, and feature ac.
Sources: GTmetrix MCP
gtmetrixmcpmcp
1 tool call
18:29
Message Claude...

GTmetrix MCP tools for AI agents

CALL ANY TOOL
9 tools covering get.
gtmetrixmcp_get_account_status
Returns the current gtmetrix account status including plan t
Returns the current gtmetrix account status including plan type, remaining api credits, next refill date, and feature access flags.
Parameters
Name
Type
Required
Description
No parameters required
gtmetrixmcp_get_catalog
Fetch a gtmetrix lookup catalog in json format for resolving
gtmetrixmcp_get_guide
Fetch a gtmetrix documentation guide in markdown format. ava
gtmetrixmcp_get_report
Retrieve the report data using the report id. contains gtmet
gtmetrixmcp_get_report_har
Fetch the raw har (net.har) for a completed gtmetrix report
gtmetrixmcp_get_report_history
Fetch historical performance data for a gtmetrix page. retur
gtmetrixmcp_get_test
Get the current status of a started gtmetrix test. long-poll
gtmetrixmcp_list_pages
List gtmetrix pages for the authenticated account. a page is
gtmetrixmcp_start_test
Start a new gtmetrix page performance test for a url.
Build your Agent
Same auth pattern across every framework.
Python · LlamaIndex
from langchain_mcp_adapters.client import MultiServerMCPClient
from scalekit import ScalekitClient

client = ScalekitClient(env_url=ENV_URL, client_id=CLIENT_ID, client_secret=SECRET)
token = client.agent.get_token(user_id="user_id", connector="gtmetrixmcp")

mcp = MultiServerMCPClient({
"gtmetrixmcp": {
"url": "https://mcp.scalekit.com/gtmetrixmcp",
"headers": {"Authorization": "Bearer " + token}
}
})
tools = await mcp.get_tools()
import OpenAI from "openai";
import { ScalekitClient } from "@scalekit-sdk/node";

const client = new ScalekitClient({ envUrl, clientId, clientSecret });
const token = await client.agent.getToken({ userId: "user_id", connector: "gtmetrixmcp" });

const openai = new OpenAI();
// Connect to MCP at https://mcp.scalekit.com/gtmetrixmcp
// Pass: Authorization: Bearer + token
import Anthropic from "@anthropic-ai/sdk";
import { ScalekitClient } from "@scalekit-sdk/node";

const client = new ScalekitClient({ envUrl, clientId, clientSecret });
const token = await client.agent.getToken({ userId: "user_id", connector: "gtmetrixmcp" });

const anthropic = new Anthropic();
// Connect to MCP at https://mcp.scalekit.com/gtmetrixmcp
// Pass: Authorization: Bearer + token
from google.adk.agents import LlmAgent
from scalekit import ScalekitClient

client = ScalekitClient(env_url=ENV_URL, client_id=CLIENT_ID, client_secret=SECRET)
token = client.agent.get_token(user_id="user_id", connector="gtmetrixmcp")
# Connect to MCP at https://mcp.scalekit.com/gtmetrixmcp
# Pass: Authorization: Bearer + token
Try these prompts
Paste any prompt into your agent to get started.
Get started
Copy the prompt
Copied
Start a new GTmetrix page performance test for a URL?
Copy the prompt
Copied
List GTmetrix pages for the authenticated account?
Advanced
Copy the prompt
Copied
Get the current status of a started GTmetrix test?
SEE HOW AUTH WORKS
User authorises once. Every agent call after uses their token with scope enforcement.
1
Authorize
Your user connects
GTmetrix MCP
once. We tie it to their identity and the meetings they approved — no shared bot account, no org-wide access
Who:
user ‘A’
when:
Once per user
access:
Limited to user
2
Store
Their
GTmetrix MCP
token lives in a vault scoped to them. User A's meetings are never reachable by an agent acting for user B, even on the same connection
vault:
encrypted
scope:
per-user
tokens:
auto-refreshed
3
Resolve
When your agent calls a
GTmetrix MCP
tool, we fetch the right token server-side. It never touches your agent, never appears in the LLM context, never shows up in your logs
speed:
~40ms
check:
before every call
seen by:
nobody
4
Audit
Every
GTmetrix MCP
tool call is logged — who triggered it, which meeting was fetched, what came back. 90 days of history, tied to the user who authorized it
history:
90 days
export:
SIEM-ready
logged:
every call
Test other agents
See the same per-user auth pattern across other connectors.
ENGINEERING
DevOps assistant agent
Triage GitHub incidents, open Linear tickets, and notify the on-call channel in Slack with context already attached.
ENGINEERING
Auto-release notes agent
Group merged GitHub PRs by feature, fix, or chore and publish release notes per tag. No manual changelog grooming.
Why Scalekit
Secure your agent's access. Connectors ship in minutes
Other connector libraries treat auth as a demo afterthought.
01.
Shared tokens break per-user analytics
A shared token looks fine in a demo. In production every call looks like a service account. Scalekit resolves the real user credential.
// shared token
audit → bot_service_account

// scalekit
audit → user_abc ✓
02.
Authentication is not authorization
03.
Multi-tenancy is architectural
04.
One connector today. Ten tomorrow.
“Our agents act across Salesforce, Gong, Google Drive, and more, on behalf of every customer. Scalekit behind the scenes meant we can keep adding tools without ever rebuilding how credentials or tool calling work.”
Venu Madhav Kattagoni
Head of Engineering / Von
FAQs
Frequently Asked Questions

Does the agent access GTmetrix as the user or as a shared key?
As the user. Each workspace member authorizes once and Scalekit resolves their credential at request time. Audit logs attribute every action to that user, not a shared service account.

Where is the GTmetrix OAuth token stored?
In Scalekit's managed AES-256 token vault, namespaced per tenant. Refresh is automatic. Revocation is a single dashboard action. Tokens never appear in prompts, logs, or LLM context.

Can I limit what the agent is allowed to do in GTmetrix?
Yes. Pass a tool name filter to listScopedTools so the DevOps agent only sees the subset you authorize. Pre-API-call scope checks block out-of-policy actions before the request reaches GTmetrix.

What happens when a user revokes GTmetrix access?
The connection is invalidated on the next tool call. Subsequent requests for that user fail closed with a clear error. Other users in the tenant remain unaffected. The event is logged for audit.

Whose GTmetrix credits do speed tests consume?
The authorizing user's. Report runs, HAR downloads, and history queries bill to that user's GTmetrix account, keeping performance testing spend visible per team member.

Start in your coding agent
Up and running in one command
Install the Scalekit skill in your editor of choice. Connector, auth, tools, prompt, all wired up
Claude Code REPL
/plugin marketplace add scalekit-inc/claude-code-authstack
/plugin install agentkit@scalekit-auth-stack
Cursor Code REPL
# ~/.cursor/mcp.json
{
""mcpServers"": {
""gtmetrixmcp"": {
""url"": ""https://mcp.scalekit.com/gtmetrixmcp"",
""headers"": { ""Authorization"": ""Bearer $SCALEKIT_TOKEN"" }
}
}
}
Codex Code REPL
# ~/.codex/config.toml
[mcp_servers.gtmetrixmcp]
url = ""https://mcp.scalekit.com/gtmetrixmcp""
auth_env = ""SCALEKIT_TOKEN""
Copilot Code REPL
# .vscode/mcp.json
{
""servers"": {
""gtmetrixmcp"": {
""url"": ""https://mcp.scalekit.com/gtmetrixmcp"",
""type"": ""http""
}
}
}