SuggestAPI

SuggestAPI expose des outils de commerce via MCP et WebMCP sur sa passerelle d'agents.

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The discovery layer

Search, understand, and discover any data.

One API for intelligent search and AI-ready discovery.

Ingest from APIs, files, feeds, and sites, or connect the search you already run. SuggestAPI accelerates search, understands the request, and returns results applications and AI agents can use.

Works with the search you already run

Algolia · Typesense · Elasticsearch · Meilisearch · Shopify

Start BuildingExplore live examples

People · Apps · AI agents

01

Discovery signal active

Live examples

Built for more than product search.

The same API covers places, parts, medications, documentation, events, and commerce.

Places & GEOTravel and directories. Resolve aliases and nearby places.E-commerceRetail. Match products, facets, and availability.Part numbersManufacturing. Match exact identifiers and partial codes.MedicationsHealthcare. Match generic names and brand aliases.Knowledge baseSaaS and docs. Retrieve articles with typeahead.EventsTicketing. Find events by time and place.

What changes

Make the search you already have understand the request.

Commerce, documentation, and industrial catalogs share one pattern. SuggestAPI turns a messy request into the constraints your existing search can use.

One use case

Commerce

“Hiking boots for Iceland in October under $250”

SuggestAPI reads

  • → Destination
  • → Season
  • → Budget
  • → Category

Docs and SaaS

Knowledge base

“How do I rotate a workspace API key?”

SuggestAPI reads

  • → Product area
  • → Task
  • → Object

Industrial catalogs

Part numbers

“316SS 1/2 in valve, 3000 PSI”

SuggestAPI reads

  • → Material
  • → Size
  • → Part type
  • → Pressure

What SuggestAPI adds

  1. 01

Understand the request

Extract constraints from natural language, whether the record is a product, a document, or a part. 2. 02

Guide your existing search

Rewrite, route, filter, and rank requests for the engine already underneath. 3. 03

Keep context across the journey

Preserve the request when someone refines, compares, or asks a follow-up. 4. 04

Return results an app or agent can use

Hand back structured matches, not only a keyword string.

Why we built this

You shouldn’t need a new discovery layer for every assistant.

People search with messy, persistent requests. Existing search drops that context after one query. You shouldn’t have to rebuild discovery for every new app or assistant.

People, apps, and agents reach SuggestAPI first. SuggestAPI understands the request and keeps that context. Your existing search finds and ranks records. Your application takes the next step.

People, apps, and AI agents reach SuggestAPI, which understands the request and keeps context. Your existing search finds and ranks records. Your application takes the next step.

Who starts

People · Apps · AI agents

↓

SuggestAPI

Understands the request · keeps context

↓

Your existing search

Finds and ranks from the index you already run

↓

Your application

Takes the next step

IntentRetrieveCompareRecommendHandoff

One layer for the request

Keep the request through the whole path.

Intent and constraint extraction, search acceleration, and agent discovery sit in front of the engine you already chose, so a new assistant doesn’t mean a new search stack, and a follow-up doesn’t mean starting over.

01 / Understand

Intent & Constraint Extraction

Extract use case, budget, timing, preferences, and constraints from natural language, then send structured filters and ranking context to the search engine you already run. No replatform.

Intent → Retrieve

Explore retrieval →

02 / Accelerate

Search Acceleration

Return relevant results fast: query rewriting, routing, caching, and delivery straight through your existing search stack.

Ask → Find

How it works →

03 / Agents

Agent Discovery

The same index, structured so AI assistants can search and act. Commerce is one path: compare, recommend, and hand off to checkout. The merchant keeps the cart.

Compare → Handoff

See protocols →

Your search and index stay where they are.

Read the full category story →

Same intent, ready for agents

Built for the agent that needs to finish the job.

Agents need the request kept intact so they can search, compare, and act without changing the index underneath. The same request arrives already interpreted, whether it is a product, a document, or a part number.

{id · title · fields}

Agent path

Intent → structure

For your stack

Keep discovery on the stack you already run.

Keep Algolia, Typesense, Elasticsearch, Meilisearch, or Shopify. SuggestAPI sits in front so you understand the request without replacing the search you already trust. If you don’t have an engine yet, index your own data.

ShopifyCommerce platformAlgoliaSearch engineClaude CommerceCommerce agentCloudflare AI SearchAgent search

Also Typesense, Elasticsearch, Meilisearch. Adapter notes in Bring Your Own Search.

For your stack

Built for the agentic web.

Meet people where they already ask.

A request that starts in ChatGPT, Gemini, a copilot, or another agent still needs structured results from the index you already have. SuggestAPI is the discovery layer that makes that handoff possible.

Agents connect over MCP and WebMCP at the SuggestAPI Agent Gateway (agent.suggestapi.com). Search tools cover the index you already run. The commerce path adds four tools: search, recommend, compare, and product lookup. A WebMCP manifest covers browser-oriented agents.

ARDUCPACPMCPA2APAPWebMCPAgent Skills

See supported protocols →

Requests that start in ChatGPT, Gemini, copilots, or other agents land on the index you already have through SuggestAPI Agent Discovery.

Your index

Discovery

SuggestAPI Agent Discovery

Agent-ready

ChatGPT · Gemini · copilots
apps · custom agents

Intent first

Hold the request, not just the query

Zero

Search migration

One API

Every backend you already run

One journey

People, apps, and agents

Capture demand your search is losing.

Add a discovery layer without replacing the stack you have.

Connect the search you already run, or index your own data. Understand the request from the first ask through the next step, for people and agents.

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