Okibi

Software teams that want AI agents to use their product today have only imperfect options: MCP integrations expose too few or too many tools and often pick the wrong one, while raw APIs force agents to build every call from scratch and sometimes get it wrong. Even when an agent can reach a product, it typically has no way to create an account, so it must stop mid-task and ask a human to sign up before it can continue. This leaves companies without a reliable way to let the growing population of AI agents actually use and pay for their product.

Okibi reads a company's repo (server code, OpenAPI specs, GraphQL schemas, or route handlers) and researches how the product is actually used, including competitor CLIs, MCP servers, and SDKs, to design a command set that matches existing tools and adds what's missing. Every candidate command is scored, built to a single standard (structured JSON output, errors that name the fix, dry-run on writes), and verified by actually running it in a cloud sandbox rather than just checking that it compiles. The result ships as a real compiled binary with generated docs and a SKILL.md file so an agent knows how to use the product immediately, and Okibi maintains the CLI as the underlying product updates. Built-in Okibi Identity lets an agent set up an account on its user's behalf, with every request carrying short-lived signed proof of who the agent is acting for, and one identity works across every Okibi-generated CLI.

The page argues that leading companies are already shipping first-party agent CLIs, positioning Okibi as the way to generate one before agents become customers.