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Create by talking to your AI service
With Arlet connected to an AI service such as ChatGPT or Claude, you can build a server right inside that conversation. There is no screen to switch to, and the tool you create is usable from the same conversation.How to create
- Connect Arlet to the AI service you use (see the pages under Connect Arlet if you haven’t yet)
- Ask for the tool you want in the conversation
- Example: “Build a tool that fetches the weather forecast for a given city from a weather API”
- The AI confirms the specification one question at a time. It asks only about what you want — what the tool should do, which service and which data it works with, which operations you need. Technical parts such as authentication and configuration are filled in by Arlet
- You’re offered 2–3 ways to build it; once you pick one, a short spec summary is presented. Approving it starts the implementation
- If a key for an external service is needed, an input panel opens inside the conversation, along with guidance on where to obtain the key (you never paste keys into the chat)
- Once deployment completes, you can call the tool from that same conversation
If you belong to more than one workspace, you’ll be asked where to create the
server. You are not asked about the implementation language — your default
from User Settings is used (Python if unset).
Editing from the conversation
After deployment, ask for a change in the same conversation and the implementation is updated. Changes are presented as a summary of what will change rather than as code, and deploy once you approve. If something goes wrong, you can roll back to the previous version.Create in the Dashboard chat
Use the Dashboard chat when you’d rather see the generated server’s details and required settings on screen as you go.How to create
- Select Create with chat in the server list on the Dashboard
- Describe the tool you want in natural language — the API to integrate with, the tools (features) you need, and what the inputs and outputs should look like. Refine the specification over the course of the conversation
- When the specification is settled, choose Build from this, review the implementation instructions assembled from the conversation, and select Run build
- When generation finishes, the panel on the right shows the server’s details and its required environment variables. Register keys for external services there
- Once every required environment variable is set, Deploy becomes available. After deploying, Open project takes you to the hosting screen
After creating
- Editing: whichever way you created it, you can keep refining the server from either the AI service conversation or the Dashboard chat
- Environment variables: keys for external APIs can be changed later from the server’s settings screen
- Editing as code: use Export to GitHub in the Dashboard settings, then simply push your changes and they deploy automatically. To use a repository you already have, see Deploy a repository
Created servers become available through the
gateway — no reconnecting and no refreshing of the
tool list required.

