From prompt to production
productecho gives your AI agent the infrastructure it needs to turn generated code into a running application. Once the MCP server is connected, your agent can work with productecho directly from the conversation.
Prerequisites
Connect productecho to your agent
Start by adding the productecho MCP server to your agent's MCP configuration. This gives the agent access to productecho's deployment capabilities.
{
"mcpServers": {
"productecho": {
"command": "npx",
"args": [
"-y",
"mcp-remote",
"https://api.productecho.com/mcp",
"--header",
"PRODUCT-ECHO-API-KEY: YOUR_API_KEY"
]
}
}
}Keep your API key private
Replace YOUR_API_KEY with your productecho API key. Never commit credentials to a public repository.
After saving the configuration, restart or reload your MCP client so it can discover the productecho server.
Ask your agent to build your app
Once productecho is connected, use your normal AI coding workflow. Describe what you want to build and let your agent generate the application.
The exact prompt is up to you. productecho is designed to sit underneath your existing AI coding workflow rather than replace it.
Ask productecho to provision the runtime
When your application is ready to run, ask your agent to provision the runtime through productecho.
Runtime provisioning
productecho handles the infrastructure and database setup required by the application. Connection details can be injected into the runtime automatically.
Get your live HTTPS URL
Once the runtime is ready, productecho provides a public HTTPS URL for your application. No manual DNS or SSL configuration is required.
If your agent can't connect
MCP server is not appearing
Check that the configuration was saved correctly and restart your MCP client.
Authentication fails
Verify that PRODUCT-ECHO-API-KEY is present and that the API key is valid.
The application is not live yet
Check the agent's deployment output and wait for runtime provisioning to complete.
What's next?
Once your first application is running, you can continue iterating through your AI agent and use productecho as the deployment runtime underneath it.