Modal MCP. Control your serverless AI infrastructure via chat.

Modal MCP Server - Audit GPU & Compute Infrastructure

Look, you gotta manage complex ML infrastructure without opening a terminal and running twenty lines of ugly CLI commands. This server connects your AI client straight to Modal's backend. It lets your agent handle the heavy lifting: checking active apps, auditing GPU deployments, and tracking persistent storage volumes—all just by talking to it.

You'll get full control over high-performance, serverless compute resources through natural conversation. Here’s what you can do with these tools:

• Checking Status: You can use list_apps to pull a rundown of every Modal application context—whether it’s running right now or if it just finished up. Need to know where your services are? Use list_deployments to get a list of all promoted, long-running service deployments on the platform.
• Storage and Security: You gotta see what's attached to your account, so you can use list_volumes to show every persistent disk network block volume connected to your project. For security checks, run list_secrets; it gives you a list of all configured secret dictionary references in your account.
• Deep Dives: If you need the nitty-gritty on one specific thing, you've got two ways to drill down. Use get_app and give it an App ID; it pulls precise JSON metadata about that single running application instance. Same deal with deployments: use get_deployment and reference a Deployment ID to get its detailed status information.
• Controlling the Compute: Sometimes you gotta hit the kill switch. If an app’s running too long and racking up bills, use stop_app. You feed it the App ID, and it forces the immediate termination of that active Modal App execution, stopping billing charges right away.

Basically, if you need to audit resources or check a status without typing out a single command, this is your ride. It gives you visibility into what's running, where it's stored, and lets you shut down runaway processes instantly.