Agentic API development: top 10 best practices
Published October 21, 2026 · By Port OS Team · Drafted with AI
An API built for developers assumes someone read the docs, wrote the client once and fixed it when it broke. An agent does none of that. It meets your API in the middle of a conversation, with a user waiting, and has to get it right from what the API tells it.
These are the practices we follow in Port OS so that assistants like ChatGPT, Claude and Muse can control devices reliably.
1. Let the agent sign itself in
If connecting needs a developer console, most users will stop there. Port OS supports OAuth with dynamic client registration and client ID metadata documents, so an MCP client can register itself and send the user straight to a sign-in page. For clients that support neither, users can register an OAuth client by hand.
2. Grant narrow permissions and check them on every call
Split read from write. In Port OS, listing devices and controlling them are separate permissions, and the user chooses which the assistant gets. Access is checked on each operation, not only at sign-in, so revoking a rule takes effect immediately. See How to set up access rules.
3. Let the agent discover what it can do at runtime
Don't make the agent assume a fixed tool list or endpoint set. An MCP client asks the Port OS server which tools it offers, and each device declares its own capabilities and accepted messages. The agent reads what is there instead of guessing from training data.
4. Publish docs written for agents
Agents read Markdown better than they navigate a docs site. Port OS publishes an llms.txt index, an agent guide library in plain Markdown, and skills for clients that only support tools. All of them come from the same source as the human docs, so they don't drift.
5. Offer a few task-shaped tools, not every endpoint
Giving an agent one tool per REST operation works, but it picks the wrong one often. Port OS exposes a small set of MCP tools shaped around tasks: one to find devices and what they support, one to send a command. The full REST API stays available for scripts and integrations.
6. Return values the agent can copy exactly
Free-form strings invite paraphrase. When the agent queries a device, Port OS returns the exact message IDs the device accepts, and the agent copies one into the control call. Enums are closed and uppercase, so there is one spelling for each value.
7. Use one error shape that says what to do next
Every Port OS error, from REST or MCP, has the same shape: a family for the broad class, a code for the specific failure and a message that says what failed and what to try next. The agent branches on the code and can show the message to the user as it is.
8. Make retries safe
Agents retry, sometimes after a timeout that hid a success. Requests that create things take an Idempotency-Key header: the same key and payload replay the original response instead of acting twice. Updates use ETags with If-Match, so an agent working from stale data gets a conflict rather than overwriting someone else's change.
9. Keep responses small by default
Large responses fill the agent's context and push out the user's request. Port OS returns device attributes only when the caller asks to expand them, and long lists page with opaque cursors. The agent asks for more when it needs it.
10. Separate "accepted" from "done"
A command the API accepted is not proof the light turned off. Port OS guides tell the agent to read fresh state after acting, and to treat a stale or unavailable reading as unknown rather than as "off". The agent then reports what actually happened.
Try it
The quick start adds a simulator light you can control without hardware. Connect your assistant with the MCP guide, and read how the Port OS MCP integration works for the details behind these choices.