Most infrastructure problems don't start with bad code. They start with missing context.
A developer waits four days for an infrastructure ticket to clear the platform team queue, not because the work is hard, but because every infra request requires a platform engineer to hand-hold a change that should have been self-service. A senior engineer spends the first hour of an incident reconstructing what changed in the environment, pulling context from the cloud console, the observability stack, and a Slack thread from three weeks ago. A new team member inherits a Terraform module with hardcoded security group IDs and naming conventions that haven't matched the production environment since last quarter's migration.
In every case, the tools weren't wrong. They just weren't talking to each other.
That's the gap the StackGen MCP is built to close.
By connecting StackGen to Cursor via the Model Context Protocol (MCP), your AI coding assistant gains live access to your infrastructure state. It knows what's deployed, what's running, and how your environment is actually configured, so when you ask it to scaffold a service, catch drift, or explain a failing deployment, it's working from reality. Not templates. Not stale exports. Your actual infrastructure.
In this post, we'll cover what StackGen is, how MCP changes what's possible in the IDE, how to connect to Cursor in under five minutes, and two high-impact use cases you can put to work immediately.
The Model Context Protocol is an open standard that gives AI tools a structured, secure way to connect to external systems and query them in real time. It's what allows Cursor or Claude, or other MCP-compatible tools, to reach outside the IDE and pull in live data, rather than working only from what's in the codebase.
Without MCP, your AI coding assistant is isolated. It can read files, suggest code, and reason about what it sees in your repository, but it has no visibility into what's actually running in your cloud environment. It can't tell you whether the module you're writing conflicts with existing IAM roles. It can't be determined whether a security group rule was changed manually last week and never committed. It can't generate a runbook that references your actual RDS endpoints, Kubernetes cluster names, or Alertmanager routing configuration.
With the StackGen MCP server running, that changes entirely. Cursor gains the ability to query real-time infrastructure state, not a snapshot or a stale export, but your live environment. StackGen MCP Server has tools like connect_resource, create_env_profile, create_appstack, get_policies, get_scan_results, scan_configuration, and more.
The practical effect is that your IDE stops being a code editor and starts being a control plane one that understands both your application and your infrastructure as a unified system.
Getting connected takes less than five minutes.
Prerequisites: You'll need the StackGen CLI installed and a Personal Access Token from your StackGen account settings.
Step 1: Open the Cursor and navigate to Settings (top right corner of the screen).
Step 2: Go to Tools & MCP and click ➕ Add Custom MCP.
Step 3: Cursor will open an MCP configuration file (typically mcp.json). Paste the following:
Step 4: Replace <YOUR_STACKGEN_TOKEN> with your actual token. Save the file and restart Cursor.
StackGen is now a live context source for Cursor's AI. Every prompt you give Cursor can draw on your actual infrastructure state alongside your codebase.
📖 Full setup details, flag descriptions, and troubleshooting at docs.stackgen.com/docs/stackgen-mcp
For the use case here, we will deploy the notification service ( a FastAPI endpoint that receives SNS-style notifications, extracts the message, forwards it to a Slack webhook, and returns success or appropriate HTTP errors if the payload is invalid or forwarding fails).
To begin the quick demo, you must first install the AWS CLI, StackGen CLI, and StackGen MCP. Once StackGen MCP is configured within Cursor, you can initiate deployment by prompting with "Deploy the notification service."
In a short time, this action will result in the creation of a new appstack, along with the corresponding topology, Infrastructure-as-Code (IaC), and necessary policies. The final step is to simply hit 'deploy' to provision the infrastructure.
Try asking Cursor: " Generate a Terraform module for a new payments microservice following the same patterns as our existing services in us-east-1."
The problem: Infrastructure modules get written once, used for one service, and never generalized. Security group IDs are hardcoded. IAM role ARNs point to resources renamed six months ago. Tagging structures don't match what the security team mandated after the last audit. When a new engineer needs to provision something, they either start from scratch or spend thirty minutes adapting someone else's module before terraform plan will even run cleanly.
The root issue isn't the engineers; it's that infrastructure context lives everywhere except where the code is being written. Every request that routes through a platform ticket queue becomes a three-to-five-day wait. Ask Cursor to scaffold a Terraform module without that context, and you get something functional but brittle, a generic template that still needs a senior engineer to adapt it to your actual environment before it's safe to apply.
With StackGen MCP: Cursor queries your live infrastructure state first. It knows your VPC IDs, subnet configurations, existing IAM roles, provider versions, and tagging policies. The module it generates belongs in your repository, follows your team's patterns, references the right resources, and doesn't need a sanity check before terraform apply.
The impact: Teams reduce the time from infrastructure request to reviewed, mergeable IaC by over 60%. Senior engineers stop being the translation layer between requirements and Terraform. Junior engineers contribute code that's safe to merge because the guardrails are built in. A platform engineer spending 40% of their sprint on ticket translation is a real cost, and it compounds with headcount. StackGen MCP flips that equation.
Try asking Cursor: " Compare our Kubernetes deployment manifests against what's currently running in the staging cluster and flag any configuration drift."
The problem: Drift accumulates silently. A manual fix at 2 am that never gets committed. A state file that doesn't sync after a pipeline update. A Kubernetes resource limit modified by a scaling event that no one intended to make permanent. A security group rule added via console access during an incident, living undocumented in production for months.
By the time it surfaces, it's a post-mortem. The incident has already happened, and the team is spending hours reconciling what terraform plan showed against what actually existed in the environment. Industry estimates put configuration drift at the root of 25–40% of cloud infrastructure outages. And that's just the operational side.
The compliance exposure is often worse. When your SOC 2 auditor asks who changed what in your infrastructure six months ago, the drift between declared state and actual state is the section that keeps platform engineers up at night. If you can't show a clean audit trail, you're exposed, and cleaning it up after the fact takes far longer than preventing it.
With StackGen MCP: Cursor compares your infrastructure code against the live environment state before anything ships. It queries StackGen to surface every discrepancy, replica counts that don't match, environment variables changed outside the pipeline, security group rules added manually, and never committed. You get a diff between intent and reality in the IDE, before the PR merges.
The impact: Drift detection moves from post-incident forensics to pre-deployment review. Teams that make this part of their development workflow, not their incident response process, report shorter MTTR and fewer repeat incidents. The compliance benefit runs in parallel: when drift is caught continuously in the development loop, your audit trail stays clean by default instead of by scramble. You're not adding a new step. You're making code review substantially more powerful.
The individual use cases above are real. But the deeper value of the StackGen MCP integration is what happens when your AI tools stop operating in isolation.
Right now, your CI/CD pipeline, cloud console, observability stack, and IDE are all generating signals, and none of them are sharing. Getting those systems to talk requires custom integrations, manual exports, or engineers who know where to look. That knowledge doesn't scale. When it lives in a few senior people, those people spend their time being human APIs between systems instead of building the platform their teams actually need.
StackGen MCP changes that architecture. When StackGen sits at the center holding your infrastructure state, your operational context, your team's policies and patterns, your AI tools get access to a unified picture. Cursor stops being a code editor and starts being an environment that understands both your application and your infrastructure as a whole.
There's an economic argument here, too. Senior platform engineers are expensive when they're answering infrastructure tickets that should be self-service, reconstructing incident timelines that should be automated, and reviewing IaC modules for basic correctness that should be guaranteed by the generation tooling. Every hour a senior engineer spends doing work that context-connected AI should be doing is an hour not spent on the architectural and automation work that actually scales the platform. StackGen MCP doesn't replace that engineer; it gives them back the hours that were disappearing into coordination overhead.
Platform engineers can enforce golden path standards from the moment code is written, not in the PR review. DevOps teams can diagnose deployment failures without switching tools. SREs can generate runbooks grounded in real system state instead of theoretical configurations that got stale the day they were written.
We built the StackGen MCP server because context-connected AI is fundamentally more useful than AI that operates on code alone. And for teams already working in Cursor, this integration is the fastest path to getting there.
StackGen is an AI-powered Autonomous Operations Platform for infrastructure and DevOps teams. We turn natural language intent into production-ready Terraform, Kubernetes manifests, and Helm charts using the context of your actual environment, not a generic starting point.
Two capabilities do the heavy lifting.
Intent-to-Infrastructure generates code that reflects your team's existing standards, naming conventions, tagging policies, security group rules, networking topology, and compliance guardrails so the output looks like your team wrote it, not like a template someone adapted.
Aiden is a suite of role-specific AI agents built for the workflows SRE, DevOps, and Platform Engineering teams actually run. Aiden for SRE surfaces remediation paths during incidents. Aiden for DevOps catches deployment issues before they reach production. Aiden for Infrastructure automates environment provisioning, golden path enforcement, and policy-as-code, the work that keeps landing on your most senior engineers.
The MCP integration brings both directly into Cursor.
Conclusion
The gap between writing code and managing infrastructure has been a source of friction, toil, and missed context for too long. With StackGen MCP connected to Cursor, your IDE becomes an environment that understands both layers — and your AI assistant becomes genuinely more capable for the work platform engineers, DevOps teams, and SREs actually do.
The two use cases here, environment-aware IaC generation, in-IDE drift detection with built-in compliance coverage, and context-rich deployment debugging, are available the moment the integration is running. The setup takes five minutes. The impact on how your team works shows up in the first week and compounds as the workflows become habits.
Ready to connect StackGen to Cursor? Start with the full MCP setup guide, or request a demo to see how StackGen fits into your broader infrastructure and platform workflow.
Also available: Aiden MCP — StackGen's AI copilot integration for SRE, DevOps, and Platform Engineering workflows directly in your AI tools.