Detect Infrastructure Drift Early Using MCP.
Someone clicked 'apply' in the Cloudflare dashboard and your Terraform state no longer matches reality , your agent finds the drift
Works with every AI agent you already use
…and any MCP-compatible client
Waiting for input…
Gemini How It Works
Your AI agent queries Terraform Cloud for workspace state , which resources are managed, what their expected configurations are, when the last successful apply ran.
Then it queries Cloudflare directly , what DNS records actually exist, what firewall rules are active, what tunnel configurations are running.
The agent compares: Terraform says api.example.com should point to 10.0.1.5. Cloudflare shows it pointing to 10.0.2.8. That is drift. Terraform does not manage a firewall rule blocking IP range 185.x.x.x , but Cloudflare has one.
That is either a manual fix someone forgot to codify or unauthorized access. Every finding goes to a Google Sheet: resource type, expected value, actual value, drift severity, when the drift was likely introduced, recommended action.
The sheet becomes your infrastructure integrity report.
MCP Server Orchestration: 3 MCP Servers, one intelligent agent
Connect Terraform Cloud, Cloudflare and Google Sheets MCP servers so your AI agent compares your Terraform-managed infrastructure state with live Cloudflare configurations and logs every drift to a Google Sheet. Teams running infrastructure-as-code who discover that someone manually changed a DNS record or firewall rule in the Cloudflare dashboard , and Terraform does not know about it , get a weekly drift audit instead of a surprise outage.
Terraform Cloud Hcp
triggerReads workspace state, run history and planned changes
list_workspaces get_current_state_version create_run show_plan Cloudflare
enrichmentPulls live zone configurations, worker routes and edge settings
list_zones list_workers list_worker_routes get_zone_analytics Google Sheets
actionLogs drift findings and remediation status to a tracking spreadsheet
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.
- Terraform Cloud Hcp, Cloudflare & 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.
Platform teams managing Cloudflare infrastructure via Terraform who need to detect manual dashboard changes before they cause incidents
DevOps engineers running weekly infrastructure audits for SOC 2 or ISO 27001 compliance
SREs investigating production issues who need to know if the infrastructure matches the last Terraform apply
Teams with multiple engineers who have Cloudflare dashboard access and need to enforce infrastructure-as-code discipline
Frequently Asked Questions About This MCP Server Orchestration
Which MCP servers do I need for this workflow?
Three: Terraform Cloud (HCP), Cloudflare and Google Sheets. Connect all three to your AI client before running any prompt from this page.
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. Connect the MCP servers and paste a prompt.
Does this run terraform plan?
No. The agent reads state and compares it with live values. It does not trigger plans or applies. You decide what to do with the drift findings.
Can I use this with AWS or GCP instead of Cloudflare?
This recipe uses Cloudflare. The Terraform Cloud MCP works with any provider , swap Cloudflare for your cloud provider's MCP to detect drift against that infrastructure.
Is my infrastructure data secure?
MCP servers authenticate through API keys. Terraform and Cloudflare data stays in your accounts. The Google Sheet is in your Drive. Vinkius does not store your infrastructure state.
MCP Servers for Global Edge Performance
Cache hit ratios monitored, edge latency tracked, WAF threats counted, performance reports delivered , run your edge infrastructure from one prompt
MCP Servers to Find Your Most Expensive APIs
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Your team has 340 hours of meetings this week across 47 events , and nobody has calculated that this costs $28,000 in engineering salaries just to sit in rooms and nod
MCP servers used in this workflow
Terraform Cloud (HCP)
Terraform Cloud (HCP) MCP Server lets your AI agent manage complex infrastructure lifecycles. You can list organizations, check workspaces, trigger runs, and inspect state outputs without leaving your chat client. It gives you fine-grained control over your entire IaC stack.
Cloudflare
Cloudflare MCP Server manages your entire edge infrastructure via AI agents. Use it to deploy Workers, manage secrets, query D1 databases, and monitor traffic across KV, R2, and CDN—all from natural language commands.
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.