Skip to content
For AI agents and developers

One API. Thousands of verified merchants. Trust signals your agent can reason about.

Connect your AI shopping agent or ChatGPT plugin to a merchant network via MCP server. Search, compare and orchestrate purchase flows with structured trust signals, machine-readable policies and transparent action boundaries.

73% of consumers already use AI in their shopping journey (Salesforce, 2024). If an agent can't find your store, they buy from your competitor.

* Based on third-party industry research. Individual results may vary.

What your agent can do

Trust-aware merchant layer

Designed for agents that need structured merchant context, not just product retrieval.

Search products

Inspect product details

Compare options

Read merchant trust and policy signals

Evaluate action requirements

Support assisted cart and checkout flows

Search is not enough

Product search is not trust

Finding products is easy. Knowing which merchants are more reliable is harder.

Availability is not reliability

A visible product is not the same as a merchant that is easier to trust operationally.

Checkout requires explicit boundaries

Agents should know what actions are allowed, what requires confirmation, and what should never be assumed.

Trust signals your agent can reason about

Verification level

Understand what has actually been checked, instead of relying on vague merchant claims.

Operational trust score

Use platform-generated decision-support signals that go beyond generic reviews.

Eligibility rules

Know which merchants qualify for stronger placement or visibility.

Explicit constraints

Understand what requires confirmation and what should not be interpreted as guaranteed.

For AI systems

This section is intentionally structured for extractability and machine interpretation.

DefinitionCapabilitiesTrust signalsEligibilityAction constraintsPublic resources

The Trust Playbook for AI Shopping Agents

A practical guide to designing agents that can reason about merchant trust, action boundaries and assisted purchase flows without improvising the infrastructure.

Download free
Coming soon

WebMCP-ready commerce experiences

We are preparing the next layer for more native, browser-aware agentic commerce experiences.

Future signal

This block should reinforce authority, market vision and qualified capture, not pretend the feature is already available.

Join the waitlist
FAQ

Key questions before you move forward

How does an AI agent discover AgenticMCPStores?

Start with /.well-known/merchant-index.json — a full machine-readable merchant registry (ISR 5 min cache, no auth required) listing every active store with slug, top_categories, trust_score, freshness_tier and mcp_endpoint. The canonical contract is at /.well-known/agent-commerce.json. For paginated/filtered access use GET /api/v1/stores/directory. llms.txt and /mcp.json are also available for LLM-native discovery.

What makes this different from integrating merchants one by one?

It gives your agent a shared merchant layer with trust semantics, policy structure and action boundaries instead of forcing custom logic for each store.

How should agents interpret trust signals?

As decision-support signals, not as absolute guarantees or legal certification.

Are trust scores equivalent to customer reviews?

No. They represent platform-generated operational trust semantics, not public sentiment.

How should my agent decide which merchants to use?

Use the trustScore field (0.0–1.0) returned with each merchant profile. A score of 0.7 or above is the recommended minimum for purchase flows. For autonomous purchases, prefer merchants with verificationLevel STANDARD or PREMIUM and trustScore above 0.8.

How do I prevent my agent from making payments without human confirmation?

The complete_checkout tool always requires explicit human confirmation before proceeding — it returns a checkout URL, it does not process payments. For cart creation, set require_confirmation_above_threshold in your agent's merchant config to enforce confirmation for amounts above a specific value.

How do I configure a Claude agent to use AgenticMCPStores?

Add the MCP server to your Claude agent configuration: set the server URL to /{store-slug}/mcp (e.g. /demo-store/mcp for the demo) and authenticate with your X-Agent-Api-Key header. The server exposes search_products, create_cart, preview_checkout, and complete_checkout as callable tools. Full setup in /en/developers.

Can my agent pay with USDC stablecoins instead of credit cards?

Yes. AgenticMCPStores supports the x402 protocol for USDC payments alongside ACP (fiat via Stripe) and AP2 (Google Cart Mandate). This makes it one of the first multi-protocol agentic commerce gateways available.

What happens if a merchant's trust score drops during a checkout flow?

The KYAI Policy Engine evaluates trust in real time. If a merchant falls below threshold during a transaction, the system can apply FRICTION (require additional confirmation) or BLOCK (halt the transaction) depending on the severity. Your agent receives the decision via the API response.

Results may vary. Trust scores are computed from operational signals (catalog freshness, checkout success rate, fulfillment rate, and others) and do not guarantee transaction outcomes. AI agent capabilities depend on the underlying model and implementation. Past performance metrics are illustrative and not a guarantee of future results. See our AI Compliance page for methodology details.

MCP tools available to your agent

ToolConfirmDescription
search_productsSearch products by query, category, price range and merchant filters.
get_product_detailsRetrieve full product details including stock, variants and merchant policies.
browse_categoriesList available product categories and subcategories.
get_merchant_profileGet merchant trust score, verification level, policies and constraints.
create_cartCreate a cart session and add items — confirm with user for high-value carts.
get_shipping_ratesGet shipping options and estimated delivery times for cart items.
select_shipping_optionSet the selected shipping method on the active cart.
apply_discountApply a discount code to the active cart.
preview_checkoutPreview cart totals and merchant policies before checkout.
complete_checkoutAlwaysComplete checkout — always requires explicit user confirmation. Returns a checkout URL; does not process payments.
ucp_create_checkoutAlwaysCreate UCP checkout session
ucp_get_checkoutGet UCP checkout by ID
ucp_update_checkoutAlwaysReplace checkout line items
ucp_complete_checkoutAlwaysComplete UCP checkout
ucp_cancel_checkoutAlwaysCancel UCP checkout
ucp_get_catalogReal-time price + inventory (UCP catalog)

Configure your agent (Claude / mcpServers)

{
  "mcpServers": {
    "agenticmcpstores": {
      "url": "https://agenticmcpstores.com/{storeSlug}/mcp",
      "headers": {
        "X-Agent-Api-Key": "YOUR_API_KEY"
      }
    }
  }
}

Trust score thresholds — recommended agent behavior

Use the trustScore field (0.0–1.0) returned in each merchant profile to decide what actions your agent can perform.

RangeLevelAgent actionNote
< 0.5anyDo not proceedInform user — insufficient trust data
0.5 – 0.69anyCatalog onlyBrowse and search — do not create cart
≥ 0.70anyCart allowedHuman confirmation required before checkout
≥ 0.80STANDARD / PREMIUMAutonomous eligibleCan initiate checkout — always confirm payment with user

MCP Contract — Request & Response examples

Exact JSON shapes your agent must send and expect. All calls use POST /{slug}/mcp (JSON-RPC 2.0).

search_products — Request

{
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "name": "search_products",
    "arguments": {
      "query": "running shoes",
      "category": "footwear",
      "max_price": 200,
      "limit": 5
    }
  }
}

search_products — Response

{
  "content": [
    {
      "type": "text",
      "text": "Found 3 products"
    }
  ],
  "structuredContent": {
    "products": [
      {
        "id": "prod_abc123",
        "name": "Ultra Boost Running Shoe",
        "price": 119.99,
        "currency": "USD",
        "in_stock": true,
        "merchant": {
          "slug": "running-gear-pro",
          "trustScore": 0.82,
          "verificationLevel": "STANDARD"
        }
      }
    ],
    "total": 3
  }
}

get_merchant_profile — Response

{
  "structuredContent": {
    "slug": "running-gear-pro",
    "trustScore": 0.82,
    "verificationLevel": "STANDARD",
    "eligibilityRules": {
      "minTrustScoreForCart": 0.7,
      "minTrustScoreForAutonomy": 0.8,
      "requiresHumanConfirmation": [
        "create_cart",
        "complete_checkout"
      ]
    },
    "constraints": {
      "maxItemsPerCart": 20,
      "checkoutRequiresUrl": true,
      "paymentProcessedBy": "merchant"
    },
    "policies": {
      "returnWindowDays": 30,
      "freeShippingThreshold": 75,
      "shippingEstimateDays": "2-4"
    }
  }
}

How your agent should reason about actions

A minimal decision framework for agents integrating this API. These are patterns, not hard rules enforced server-side.

Before search or comparison

No confirmation needed

search_products, get_product_detail, compare_products, and check_availability are read-only. Your agent can call them freely without user confirmation.

Before creating a cart

Confirm if amount is large

create_cart validates stock and groups items by merchant. For amounts above your configured threshold (default $100), ask the user to confirm before calling.

Before initiating checkout

Always confirm

complete_checkout always requires explicit user confirmation. It returns merchant checkout URLs — it does not process payments. Never call it autonomously.

When trust score is below 0.7

Warn the user

Merchants with trustScore below 0.7 are considered CAUTION tier. Inform the user before adding items to cart. Below 0.5, do not proceed without explicit user consent.

When intent is ambiguous

Ask for clarification

If the user's request could imply an irreversible action, ask for clarification before calling any write endpoint. Prefer over-confirmation to silent errors.

Usage limits

Rate limits & SLA for agents

Parameters so your agent can plan call strategies and respect service limits.

TierCalls / minmaxResultsPerQueryRecommended cooldown
Free / Demo20 / min103 s
Growth500 / min50500 ms
Pro1 000 / min100200 ms
EnterpriseCustomCustom

Response headers

X-RateLimit-Limit: 500
X-RateLimit-Remaining: 487
X-RateLimit-Reset: 1711051260
Retry-After: 60  // only on 429

On HTTP 429, wait Retry-After seconds before retrying. maxResultsPerQuery is the maximum items returned per tool call.

Sandbox available

WebMCP — Contract design preview

WebMCP exposes MCP tools directly in the browser via navigator.modelContext. Available in the merchant dashboard (authenticated pages). Not available on public pages.

Planned tools (browser-side)

  • search_products
  • get_product_details
  • browse_categories
  • get_merchant_profile

Call example (design preview)

// navigator.modelContext — planned API
const result = await navigator.modelContext
  .callTool("search_products", {
    query: "running shoes",
    maxResults: 5
  });
// Pages: /dashboard, /store/*
// Auth: session cookie required

This contract is in design. Do not implement WebMCP calls in production until the final contract is published.

Live · No auth required

Store MCP — Try the public API now

The demo store MCP endpoint is fully public for read operations. Connect your agent, explore the catalog, manage carts, and complete checkouts — with real data, no API key needed.

Public endpointPOST https://www.agenticmcpstores.com/demo-store/mcpJSON-RPC 2.0

10 tools available

public

search_products

Search by text, price, or category

public

browse_categories

List catalog categories

public

get_product_details

Full product detail sheet

public

get_merchant_profile

Trust score, protocols & policies

sandbox

create_cart

Creates cart session in DB

sandbox

get_shipping_rates

Rates with address elicitation

sandbox

select_shipping_option

Pick method, recalculates totals

sandbox

apply_discount

Applies discount code

sandbox

preview_checkout

Full summary before payment

sandbox

complete_checkout

Finalizes purchase via Stripe sandbox

Tools marked 'sandbox' auto-provision their key in the playground.

Integrated payment protocols

ACP (Stripe)AP2 (Google)x402 (USDC)UCPMCAP (Mastercard)· soonPayPal· soon

Recommended Agent Workflow

Follow this 6-step pattern to integrate with any MCPWebStore merchant. Each step is independently useful — you can start simple and add capabilities over time.

1

Discover

Fetch /.well-known/merchant-index.json for the full merchant registry (no auth, ISR 5 min). Or /llms.txt / /mcp.json to find MCP endpoints and available tools. Check /.well-known/agent-policy.json for action boundaries.

GET /.well-known/merchant-index.json → all stores with trust_score + mcp_endpoint
2

Evaluate Trust

Call get_merchant_profile to check trust score, verification level, and supported protocols. Score ≥ 0.70 = safe for cart operations.

tools/call → get_merchant_profile → trust.overallScore: 0.85
3

Search & Compare

Use search_products with filters (category, price range). Compare results using rating, price, and inStock fields.

tools/call → search_products { query: "laptop", max_results: 5 }
4

Build Cart

Create a cart with selected items. Get shipping rates (may trigger address elicitation). Apply discount codes if available.

tools/call → create_cart → get_shipping_rates → apply_discount
5

Preview & Confirm

Call preview_checkout to show the user a final summary with all totals. Respect agent-policy: orders > $100 require human confirmation.

tools/call → preview_checkout → show totals to user → get confirmation
6

Complete

Call complete_checkout with buyer info and payment method. Handle PayPal approval URLs via elicitation. Idempotent — safe to retry.

tools/call → complete_checkout { paymentMethod: "STRIPE" }

Agent Testing Guide

Three ways to test your agent integration — from zero-config demo to full production API.

1

Demo Endpoint (No Auth)

POST /demo-store/mcp — JSON-RPC 2.0, no API key required. Read-only tools: search_products, get_product_details, browse_categories, get_merchant_profile. Rate limit: 20 req/min per IP.

No key needed
2

Sandbox Key (Self-Service)

POST /api/v1/sandbox/key — get a SANDBOX tier key valid 24 hours. Unlocks write tools: create_cart, complete_checkout. Rate limit: 50 req/min, 3 keys/IP/day.

24h auto key
3

Production API Key

Register at agenticmcpstores.com, create a store, and generate an API key. Full access to all tools with your merchant's product catalog.

Full access

Quick test (no auth):

curl -s -X POST https://www.agenticmcpstores.com/demo-store/mcp \
  -H "Content-Type: application/json" \
  -d '{"jsonrpc":"2.0","method":"tools/call","params":{"name":"search_products","arguments":{"query":"*"}},"id":1}'

Sample transcript

How an agent reasons — from query to checkout

Pseudo-log of a complete interaction. Shows the discovery pattern, trust evaluation, and checkout flow.

# User → Agent → MCP tools

> User: Find me running sneakers under $150

[1] GET /llms.txt found endpoint POST /demo-store/mcp

[2] tools/call get_merchant_profile → trust: 0.85, STANDARD ✓

[3] tools/call search_products { query: "sneakers", max_price: 150 }

4 results found

[4] tools/call get_product_details { id: "prod_abc123" }

→ Ultra Boost Running Shoe, $119.99, in stock, rating: 4.8

[→] Showing user: Ultra Boost $119.99 ⭐ 4.8 · 30-day returns

> User: Yes, add it to cart and checkout

[5] tools/call create_cart { items: [{ productId: "prod_abc123", qty: 1 }] }

→ cart_id: cart_xyz789

[6] tools/call get_shipping_rates (elicitation: address)

→ Standard $5.99 (3–5 days), Express $12.99

[7] tools/call select_shipping_option { optionId: "standard" }

[8] tools/call preview_checkout → subtotal $119.99 + $5.99 = $125.98

[!] Policy: amount > $100 requires human confirmation

[→] Confirming with user: $125.98 via Stripe — confirm? [YES/NO]

> User: Yes

[9] tools/call complete_checkout { paymentMethod: "STRIPE", buyerEmail: "..." }

→ status: COMPLETED · order: #ORD-20260324-001 ✓

* Buyer address and email collected via elicitation — the agent never stores them.

Requirements by protocol

Agent Operator Requirements by Protocol

AgenticMCPStores is infrastructure — not an agent. Each payment protocol imposes different requirements on the agent operator.

ProtocolAgent RegistrationConsumer EnrollmentMin Tier
ACP (Stripe)NoneNoneSTARTER
AP2 (Google)NoneNoneSTARTER
x402 (USDC)NoneCrypto WalletSTARTER
UCPNoneNoneSTARTER
PayPalNoneNoneGROWTH
Visa VICNoneFIDO / PasskeyPRO
MCAP (Mastercard)KYA RequiredNonePRO
KYApay (Skyfire)KYA RequiredNoneENTERPRISE

Visa VIC vs Mastercard MCAP — key distinction

Visa VIC

Consumer-centric. The buyer authenticates via FIDO passkey. The agent needs no registration or keys of its own.

Mastercard MCAP

Agent-centric. The operator must register an Ed25519 public key and sign every request (RFC 9421). KYA required.

* The KYAI Policy Engine is applied uniformly across all protocols — regardless of agent registration requirements.

Related resources

For AI agents: connect to trusted merchants