Lambda CLI is an unofficial command-line interface and MCP server designed for efficiently managing Lambda cloud GPU instances, offering automation and AI assistant integration.

What notification options are available for instance readiness?

Lambda CLI supports configurable notifications to Slack, Discord, or Telegram, alerting you when your GPU instances are ready and SSH-able.

How can I manage my GPU instances with Lambda CLI?

You can use direct CLI commands (list, start, stop, find) or integrate it with AI assistants via the MCP server to control your Lambda GPU infrastructure.

Is Lambda CLI an official tool from Lambda?

No, Lambda CLI is an unofficial, community-built project and is not affiliated with or endorsed by Lambda.

Does Lambda CLI support automated instance launching?

Yes, it features automatic polling for GPU availability and can auto-launch instances based on your specified criteria, streamlining the provisioning process.

Lambda CLI

Name: Lambda CLI
Author: Strand-AI

•

Provides an unofficial command-line interface and MCP server to efficiently manage Lambda cloud GPU instances.

Lambda CLI offers a powerful, community-built solution for interacting with Lambda cloud GPU instances. It provides a fast command-line interface (`lambda`) for direct terminal control over GPU instance lifecycle, from listing available types to starting, stopping, and polling for availability. Additionally, it includes an MCP server (`lambda-mcp`) that enables AI assistants like Claude to seamlessly manage your GPU infrastructure, streamlining automation and operational tasks.

主な機能

01Configurable notifications (Slack, Discord, Telegram) for instance readiness

02MCP server integration for AI assistants to control GPU infrastructure

0318 GitHub stars

04Direct CLI for managing Lambda GPU instances (list, start, stop, find commands)

05Automatic polling for GPU availability and auto-launching of instances

06Flexible authentication methods, including environment variables and secret commands

ユースケース

01Automate the waiting and launching of specific GPU types for on-demand compute needs

02Provision and deprovision Lambda GPU instances directly from the terminal for development or research

03Enable AI assistants to orchestrate and manage cloud GPU resources for automated workflows