Shared cloud environments for teams building with AI agents
Every developer on the same environment, MCP servers and context files. Onboard in minutes. Agents run continuously. No more copying .env files and CLAUDE.md around.
Every developer has a different setup. Agents can’t share context. Onboarding takes days.
When everyone runs Claude Code locally, context lives on individual machines. A new developer has to clone the repo, install Claude Code, configure MCP servers, copy the CLAUDE.md and .env files, and spend half a day getting to the same starting point. And when an agent produces something useful on one machine, sharing it means copy-pasting files over Slack. CloudCLI makes the environment itself the shared artifact.
One environment setup, shared across your whole team
Configure once. Everyone starts from the same baseline — with AI agents ready to run.
Configure a shared base environment
Set up your MCP servers, API keys, context files and tools once. This becomes the baseline every team member starts from.
Each developer gets an isolated container
Every team member gets their own isolated environment forked from the base. Same tools, same context, separate work. No conflicts, no credential sharing.
Agents work in parallel across the team
Multiple developers run Claude Code, Cursor CLI or Codex simultaneously on different tasks. Sessions persist in the cloud. Agents keep working even when developers step away.
Share MCP servers and tool configurations across your whole team
MCP servers for GitHub, Linear, Slack and your internal tools are configured once and shared across the team's environments. Every developer's Claude Code instance connects to the same tools without any individual setup. When you add a new MCP server, it's available to everyone immediately.
Onboard a new developer in 5 minutes, not 5 hours
Invite a new developer and they get an environment with the full stack pre-configured — the right Node version, the right Python version, all your MCP servers connected, your CLAUDE.md loaded, and Claude Code ready to run. No README to follow, no local setup friction, no 'works on my machine' problems. They're writing code with an AI agent within minutes.
More ways to build with AI agents
If your team is currently paying for GitHub Codespaces, see how CloudCLI compares as a GitHub Codespaces alternative built specifically for AI coding agents. And when you want to go fully async, background coding agents let your whole team trigger tasks from Linear or Jira and come back to finished code.
Frequently asked questions
Common questions from engineering leads evaluating CloudCLI for their team
Yes. Every developer gets their own isolated container with dedicated compute and filesystem. They share the base configuration but run independently — no conflicts, no accidental access to another developer's files.
API keys are encrypted at rest and shared through the environment configuration. Individual developers can also add their own keys. Credentials are never exposed in plaintext in logs or environment variables.
Yes. Each CloudCLI environment has SSH access, so developers can connect from VS Code, Cursor, JetBrains or any SSH-capable IDE. The web UI is also available for quick access from any browser.
We charge per environment. Each developer on your team gets their own environment at a flat monthly rate. Team plans include shared environment templates and centralized billing. Contact us for volume pricing.
Yes. Different developers can run Claude Code, Cursor CLI or Codex on different tasks simultaneously — each in their own isolated environment. Sessions persist in the cloud, so agents keep working even when developers step away or sleep.
Yes. CloudCLI has a REST API that lets you trigger coding tasks programmatically from Linear, Jira, n8n or any automation pipeline. A ticket moves to 'In Progress' and an agent starts working on it immediately.
Give your whole team AI-first cloud environments
Start with a free trial. No credit card required. Enterprise pricing available.