Generic bridge package that automatically turns any oRPC backend into browser-native AI tools via the WebMCP spec — zero per-endpoint configuration required.
WebMCP is an emerging W3C Community Group specification that brings AI tool integration directly into the browser. This demo app shows how a Next.js application with an oRPC backend can expose its API routes as WebMCP tools — letting AI agents call them natively from within Chrome.
The project includes a reusable bridge package (orpc-webmcp) that automatically registers backend procedures as browser-accessible tools, with zero manual configuration per endpoint.
navigator.modelContext API in Chrome Canary (146+)Write type-safe backend procedures with oRPC and Zod schemas — standard API development, nothing WebMCP-specific.
The orpc-webmcp bridge automatically discovers all procedures and registers them as WebMCP tools via navigator.modelContext.
Any AI agent running in the browser (like Chrome's built-in AI) can discover and call your API endpoints as tools.
Tool calls are validated against Zod schemas, executed server-side via oRPC, and results returned to the agent — fully type-safe.
WebMCP works today in Chrome Canary with the built-in Gemini Nano model. Here's how to try it:
chrome://flags/#web-mcp and set it to Enabledgit clone https://github.com/Mark-Life/webMCP-example && cd webMCP-example && bun install && bun devhttp://localhost:3000 in Chrome Canary — the app automatically registers its tools via navigator.modelContextNo polyfills needed — the app uses the native navigator.modelContext API (Chrome 146+).
The demo task manager exposes five tools to AI agents:
apps/web/ — Next.js application with UI, server actions, and oRPC route handlerpackages/orpc-webmcp/ — Reusable bridge package with core logic and React hooksThe orpc-webmcp package is the core innovation — a generic adapter that:
navigator.modelContextThis means any oRPC application can become WebMCP-compatible by adding a single hook.



WebMCP Demo is an open-source project. It serves as both a reference implementation for the WebMCP specification and a starting point for building browser-native AI integrations.