Three Ways to Let AI Agents Operate Your Product: MCP, WebMCP, and CLI

As AI agents increasingly act as end users, product teams need to decide how those agents can actually complete tasks on a user's behalf, not just discover features. This talk introduces Agent Experience (AX) and compares the three main doors agents can use to execute tasks — MCP servers, WebMCP, and existing command-line interfaces — covering how each one works in live demos.

■ Agent Experience (AX) and Why It Matters
- The gap between an agent finding a feature and being able to authenticate and complete a task for the user
- Traffic data cited from Vercel and Cloudflare on the growth of AI bot traffic relative to human web traffic
■ The Three Doors: How Agents Execute Tasks
- MCP: agent-facing interface layer with structured tools, local or remote servers, and a unified OAuth 2.1 authorization path
- WebMCP: lifting a site's existing HTML/JavaScript capabilities into a programmatic tool layer, demonstrated with ChatGPT interacting with a website
- CLI: reusing already-installed command-line tools through an agent, demonstrated with deploying an application via terminal commands
■ Comparing the Doors
- Capability leverage, user-visible feedback, access control and authentication, distribution channels, and composability across the three approaches
- Guidance that the choice of door is an AX decision based on your audience's capabilities, preferred distribution, and integration needs
- Quick design tips for MCP servers and CLI interfaces, plus a mention of WebMCP's experimental status and upcoming release

This session is aimed at developers, product teams, and engineers building agent-accessible products. Viewers will come away with a framework for choosing between MCP, WebMCP, and CLI, along with practical design tips for exposing their own services to agents.