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TL;DR

uvx mcp-agent login
uvx mcp-agent deploy my-agent
uvx mcp-agent cloud servers describe my-agent
That is enough to put any MCP application—mcp-agent workflow, FastMCP server, or ChatGPT App backend—online. Deployments automatically run on the managed Temporal cluster; you do not need to configure Temporal hosts or queues yourself. The sections below add a little context and point to deeper guides when you are ready.

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1. Authenticate (one time)

uvx mcp-agent login
The CLI opens a browser window so you can sign in with GitHub or Google and generate an API key. Credentials are cached under ~/.mcp-agent/credentials.json. In CI, set the MCP_API_KEY environment variable instead.

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2. Confirm your project layout

Minimal structure: 
my-agent/
├── main.py
├── mcp_agent.config.yaml
└── (optional) mcp_agent.secrets.yaml
mcp_agent.config.yaml just needs to describe your app. You can keep execution_engine: temporal if you already use it locally, but the cloud service will always launch your code on Temporal automatically. Example:
mcp_agent.config.yaml
name: web_summarizer
logger:
  transports: [console]

mcp:
  servers:
    fetch:
      command: "uvx"
      args: ["mcp-server-fetch"]

openai:
  default_model: gpt-4o
If your app needs API keys, place them in mcp_agent.secrets.yaml (details in Manage secrets).

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3. Deploy

uvx mcp-agent deploy web-summarizer
The CLI bundles the current directory, prompts you to classify secrets (deployment vs. user), uploads the bundle, and provisions the runtime. On success you will see something like: 
✓ Deployed app ID: app_abc123xyz
   Server URL: https://app_abc123xyz.deployments.mcp-agent.com
   Status: ONLINE
Redeploy with the same name to ship updates. Useful flags:
  • --config-dir <path> – deploy from another directory.
  • --non-interactive – reuse stored secrets (CI/CD).
  • --dry-run – validate without uploading.

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4. Check status & logs

uvx mcp-agent cloud servers describe app_abc123xyz
uvx mcp-agent cloud logger tail app_abc123xyz --follow
describe prints the endpoint, auth mode, and worker status. logger tail streams application logs; add --since 30m or --grep "ERROR" as needed. All other operational commands are listed on the cloud overview.

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5. Configure clients

Most deployments need per-user credentials. Prompt users (or your CI job) with: 
uvx mcp-agent cloud configure --id https://app_abc123xyz.deployments.mcp-agent.com
Then install the server into your favourite MCP client:
  • Claude Desktop / Cursor / VS Code / ChatGPT – uvx mcp-agent install --client <client> https://app_abc123xyz.deployments.mcp-agent.com/sse
  • ChatGPT Apps – deploy with --no-auth and register the SSE endpoint in the Apps dashboard.
  • Python – add the server endpoint to your MCP client config (see guide).

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Going further

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