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Sanity

Announced

Headless CMS with real-time collaboration, a GROQ query language, and a hosted Content Lake used by developers to build structured content backends with schema-as-code tooling.

Sanity has announced plans to support UCP as a participant. No public endpoint is available yet.

Sanity is a headless CMS platform built around structured content. Its content backend is called the Content Lake: a cloud-hosted document store where teams define schemas in code and the platform manages persistence, versioning, and delivery. The Sanity Studio is a customizable open-source editing environment built on React that developers configure to match their content model.

Sanity's query language is GROQ (Graph-Relational Object Queries), a purpose-built language for querying the Content Lake. GROQ expressions can filter, join, project, and transform documents in a single query, returning exactly the data shape the client needs. The GROQ API endpoint is CDN-backed for read performance.

The platform supports real-time collaboration through a presence and patching system. Editors see each other's cursors and changes live. Sanity's portable text format handles rich text content as structured data rather than HTML, making it straightforward for agents to parse and display in non-HTML rendering contexts.

Sanity is used by e-commerce brands, media companies, and SaaS products. Its schema-as-code approach means the content model is version-controlled and reviewable. Types can reference other types, creating rich document graphs: a product document references variant documents, which reference image assets and category documents.

For agents, Sanity's GROQ API is powerful for complex content retrieval. Agents can write GROQ queries that traverse document relationships, filter by field values, and return denormalized content in a single request. In composable commerce architectures, Sanity often serves as the product content layer. Sanity is actively exploring how AI agents interact with structured content, including native AI integrations in the Studio and API patterns optimized for AI content workflows. The schema-as-code model means agents can read the content schema directly from the codebase to understand available fields.

Why This Matters for UCP

Sanity provides structured product content and document graphs through its GROQ API and Content Lake, enabling agents to query complex content relationships in composable commerce stacks with a single expressive query.

UCP Endpoint

Announced — Endpoint not yet publicly available

Integration Example

// Sanity GROQ API for structured content retrieval.
// Agents write GROQ queries to fetch document graphs from the Content Lake.

import { createClient } from '@sanity/client';

const client = createClient({
  projectId: process.env.SANITY_PROJECT_ID,
  dataset: process.env.SANITY_DATASET,
  apiVersion: '2024-01-01',
  useCdn: true,
});

// Query in-stock products with resolved references using GROQ
const products = await client.fetch(
  `*[_type == "product" && defined(slug.current) && inStock == true] {
    _id,
    name,
    "slug": slug.current,
    price,
    description,
    "categories": categories[]->{ name, "slug": slug.current },
    "imageUrl": mainImage.asset->url
  } | order(price asc) [0...20]`
);

console.log('Products fetched:', products.length);
console.log('First product:', products[0]?.name, 'at', products[0]?.price);

UCP Status

Announced

Tags

headless-cmsstructured-contentreal-timedeveloper-tools

Pricing

freemium

Added 2026-04-23
Verified2026-04-23
Documentation

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Reviews

★★★★★4.7 (3 reviews)

These are illustrative examples to show what reviews will look like. Submit your own experience below.

JS

J. Santos

Senior Engineer · Feb 28, 2026

★★★★★

Integration was straightforward. The UCP endpoint discovery works as documented and checkout completes in under 2 seconds.

ML

M. Lee

Backend Developer · Mar 3, 2026

★★★★

Works well for our use case. The documentation is accurate and the implementation matches what the spec describes.

RK

R. Kapoor

Platform Engineer · Jan 15, 2026

★★★★★

Integrated in an afternoon. Solid implementation with no unexpected edge cases in production.

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