Track Frontend Performance Budgets via MCP.
Deploys tracked, performance budgets enforced, Lighthouse scores logged, regressions flagged , guard your Core Web Vitals without manual audits
Works with every AI agent you already use
…and any MCP-compatible client
Waiting for input…
Gemini How It Works
Your AI agent reads Netlify: new production deploy completed , Build #847 for web-app, committed by @alex, build time 2m 34s.
The agent triggers Checkly performance checks on the production URL. Results: LCP 2.1s (budget: < 2.5s ), CLS 0.08 (budget: < 0.1 ), INP 180ms (budget: < 200ms ), FCP 1.2s, TTFB 340ms.
All within budget. But the agent compares to last deploy: LCP was 1.6s, now it is 2.1s , a 31% increase.
Still within budget, but trending toward the limit. CLS improved from 0.12 to 0.08 , the layout shift fix worked.
The agent logs to Google Sheets: Build #847 row with all metrics, deploy timestamp, commit hash, author. After 20 deploys, you see the LCP trend: 1.41.51.61.82.1.
Three more deploys at this rate and you will blow the 2.5s budget. The agent flags it: 'LCP trend alert: 5 consecutive increases.
Will exceed 2.5s budget within ~3 deploys at current rate.'
MCP Server Orchestration: 3 MCP Servers, one intelligent agent
Connect Netlify, Checkly and Google Sheets MCP servers so your AI agent monitors every Netlify deploy, triggers Checkly performance checks against your production URL, compares the results to your performance budget (LCP < 2.5s, CLS < 0.1, INP < 200ms), and logs results to a Google Sheet for trend analysis. Frontend teams who care about Core Web Vitals but forget to run Lighthouse after every deploy get automated enforcement. No manual audits. No performance regressions slipping through. One prompt and your performance budget is enforced.
Netlify
triggerMonitors production deploys and build metadata
list_deploys get_deploy get_site trigger_build Checkly
actionRuns synthetic performance checks and measures Web Vitals
trigger_check_run get_check_details get_check_performance_metrics list_checkly_checks Google Sheets
actionLogs performance scores and tracks trends over time
append_sheet_values update_sheet_values get_spreadsheet create_spreadsheet Run This Automation Today
Connect Claude, ChatGPT, Cursor, or any AI agent to the Vinkius catalog and run this automation in minutes.
Build Your Own MCP
Turn any internal API into an MCP server. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Connect & Automate
The 3 servers this recipe uses are ready in the catalog. Connect them once, paste a prompt, and your AI runs the full workflow.
- Netlify, Checkly & Google Sheets ready in the catalog right now
- Add more from 4,700+ servers whenever you need
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers and recipes added every week
Superpowers you didn't know your AI had
The Vinkius catalog gives your agent access to 4,700+ MCP servers and the intelligence to combine them. Imagine never logging into another dashboard. Your AI handles the work across every tool, in one conversation. That's what this infrastructure was built for.
Cross-Platform Intelligence
Your agent doesn't just connect to tools. It understands the relationships between them. Data flows where it needs to go, automatically, with full context preserved across every platform.
Contextual Reasoning
Every decision your agent makes considers the full picture. It reads CRM data, checks calendars, reviews conversation history, and acts on everything at once. Not step by step. All at once.
Productivity at Scale
What used to take 45 minutes across five different dashboards now takes one sentence. Your agent runs the entire workflow end to end while you focus on decisions that actually matter.
Zero-Config Reliability
No API keys to paste. No webhooks to configure. No YAML to debug. Connect your MCP servers once, and your agent handles the rest. Every time, without intervention.
Made for
exactly this
Your AI agent taps into the entire Vinkius MCP catalog to handle these for you. You describe what you need. It does the rest.
Frontend teams who need automated Core Web Vitals enforcement after every Netlify deploy without manual Lighthouse runs
Performance engineers who want historical tracking of LCP, CLS and INP trends across every production deploy
Engineering managers who need to prove performance compliance for SLAs or SEO requirements with documented metrics
Agencies managing multiple client sites on Netlify who need per-site performance budgets tracked in a shared spreadsheet
Frequently Asked Questions About This MCP Server Orchestration
Which MCP servers do I need for this workflow?
Three: Netlify, Checkly and Google Sheets. Connect all three to your AI client.
Does this work with Claude Desktop, Cursor or Windsurf?
Yes. Any AI client that supports the Model Context Protocol works , Claude Desktop, Cursor, Windsurf, Cline and others.
Can I use Vercel instead of Netlify?
Yes. Replace the Netlify MCP server with the Vercel MCP server. The workflow logic remains identical.
What performance budgets should I set?
Google recommends: LCP < 2.5s, CLS < 0.1, INP < 200ms for 'Good' Core Web Vitals. Adjust based on your application's needs.
Does Checkly measure real user metrics?
Checkly runs synthetic checks from controlled environments. For real user metrics (RUM), pair with a RUM tool. Synthetic checks ensure consistent baseline measurements.
Can I get alerts when a budget is violated?
Yes. Add Discord or WhatsApp to the workflow. The agent will post an alert when any metric exceeds its budget threshold.
Catch Frontend Downtime Early Using MCP Servers
Your landing page passed the Lighthouse audit but your checkout flow takes 11 seconds in Brazil because nobody runs synthetic checks from outside us-east-1
Deploy Containers to Production Using MCP
Code pushed, images built, tags verified, deploys triggered, status reported , ship containers from commit to production in one prompt
MCP Recipe for Faster Incident Response
Endpoints monitored, failures detected, incidents auto-created, root cause traced to the commit , respond to outages before users tweet
Benchmark Seed Valuations Using MCP Servers
Your portfolio valuations compared, market comps pulled, benchmark report built , know if $12M pre-money for a Seed is reasonable before you negotiate
Book Appointments via WhatsApp Using MCP
Your AI agent checks availability, sends time slots via WhatsApp and logs every booking
Build Serverless Data Warehouses Using MCP
You scrape data into CSV files that nobody queries , Firecrawl extracts structured web data, Neon stores it in serverless PostgreSQL you can query with SQL, and Sheets visualizes the results
MCP servers used in this workflow
Netlify
Netlify MCP Server manages your entire Netlify deployment lifecycle directly from any AI agent. Use this to list all active sites, trigger new builds instantly, track historical deployments, and monitor form submissions without touching the dashboard. You can query site metadata, check user profiles, and manage DNS zones—all via conversation.
Checkly
Checkly connects your AI agent directly to application monitoring and E2E testing data. You can list all configured API endpoint checks, run immediate system health tests, and get performance metrics on demand—all through natural conversation. It handles everything from uptime tracking to auditing alert channels.
Google Sheets
Google Sheets MCP Server lets your AI client read, write, and manage data directly in Google Sheets. Use conversational commands to pull data from specific ranges, append new rows, or structure entire spreadsheets. It acts as an analyst, letting you manipulate complex data without opening the GUI or writing formulas.