Searchspring
EcosystemEcommerce search, merchandising, and personalization platform with REST APIs for product discovery and faceted navigation. Used by mid-market and enterprise retailers for site search with configurable merchandising rule layers on top of algorithmic ranking.
Searchspring provides site search, category merchandising, and personalization for ecommerce retailers. The platform indexes product catalogs and exposes search and browse APIs with faceted navigation, spell correction, synonym management, and merchandising rules that retailers configure to promote specific products or product groups.
The merchandising layer is a core differentiator. Retailers configure rules that boost, bury, or pin products in search results based on business logic: promotion schedules, inventory thresholds, margin targets, or manual curation. Agents querying Searchspring results receive rankings that reflect both algorithmic relevance and merchandiser intent.
Searchspring's personalization adjusts rankings based on individual shopper behavior. The platform tracks click and purchase events and uses them to rerank results for returning shoppers. Agents that pass user session context receive personalized rankings that incorporate the buyer's preferences alongside baseline relevance and merchandising rules.
The REST API covers search, autocomplete, and recommendations. The search endpoint returns full product data, facet counts, and pagination metadata. The recommendations endpoint returns related products, trending items, and recently viewed products by strategy. Both endpoints are designed for server-side integration, making them accessible for agent workflows that run outside browser context.
Why This Matters for UCP
Searchspring provides ecommerce search and merchandising APIs that agents use to discover products through merchant-configured ranking rules, returning product data shaped by both algorithmic relevance and retailer business logic before UCP checkout.
UCP Capabilities
UCP Endpoint
Ecosystem — Endpoint not yet publicly available
Integration Example
// Searchspring REST API for product search and recommendations.
// Agents query with facets and receive merchandiser-adjusted rankings.
const siteId = process.env.SEARCHSPRING_SITE_ID!;
const searchBase = 'https://' + siteId + '.a.searchspring.io/api/search/search.json';
// Product search with facet filters
const searchParams = new URLSearchParams({
q: 'denim jacket',
resultsFormat: 'native',
resultsPerPage: '10',
});
searchParams.append('filter.availability', '1');
searchParams.append('filter.gender', 'women');
const results = await fetch(searchBase + '?' + searchParams).then(r => r.json());
console.log('Total results:', results.pagination?.totalResults);
results.results?.forEach((product: any) => {
console.log(product.name, '$' + product.price, 'ID:', product.id);
});
// Get product recommendations
const recoBase = 'https://' + siteId + '.a.searchspring.io/boost/' + siteId + '/recommend';
const recommendations = await fetch(recoBase, {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({
tags: ['also-bought'],
product: results.results?.[0]?.id,
limits: { 'also-bought': 5 },
}),
}).then(r => r.json());
console.log('Recommendations:', recommendations?.[0]?.results?.length);Category
Search & DiscoveryUCP Status
EcosystemTags
Pricing
enterprise
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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.
R. Kapoor
Platform Engineer · Jan 15, 2026
Integrated in an afternoon. Solid implementation with no unexpected edge cases in production.
J. Santos
Senior Engineer · Feb 28, 2026
Integration was straightforward. The UCP endpoint discovery works as documented and checkout completes in under 2 seconds.
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.
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