Use with AI SDK

The Stitch SDK ships a dedicated adapter for the Vercel AI SDK. Import stitchTools() from the /ai subpath and drop it directly into generateText() or streamText(). The LLM handles tool orchestration-you just write the prompt.

Install

You need three packages:

npm install @google/stitch-sdk ai @ai-sdk/google

Set your keys

export STITCH_API_KEY="your-stitch-api-key"
export GOOGLE_GENERATIVE_AI_API_KEY="your-gemini-api-key"

Basic usage

import { generateText } from "ai";
import { google } from "@ai-sdk/google";
import { stitchTools } from "@google/stitch-sdk/ai";

const { text } = await generateText({
  model: google("gemini-3.1-flash-lite-preview"),
  tools: stitchTools(),
  maxSteps: 5,
  prompt: "Create a new Stitch project called 'Landing Page' and generate a hero section with a CTA button.",
});

console.log(text);

The LLM will call create_project, then generate_screen_from_text, then return a natural language summary of what it built. You don’t need to write any orchestration logic.

Filter tools

If you want to restrict which tools the model can access, pass an include array:

const tools = stitchTools({
  include: ["create_project", "generate_screen_from_text", "list_projects"],
});

This is useful for tightening the model’s scope-for example, preventing it from deleting projects.

Override the API key

If you don’t want to rely on the STITCH_API_KEY env var, pass it directly:

const tools = stitchTools({ apiKey: "your-key-here" });

How it works

stitchTools() returns a Record<string, Tool> that is directly compatible with the AI SDK’s tool format. Each tool is pre-wired with an execute function that calls the underlying Stitch MCP server. The adapter has zero runtime dependency on the ai package-it only imports the Tool type.

For a deeper look at the architecture, see Architecture.