# La Luer — AI Skincare Commerce (remote · searchshopai-mcp.fly.dev)

Search, compare, and purchase La Luer microcurrent facial devices and skincare products.

- Trust score: 66/100 (medium)
- Change this week: +7
- Registry status: deprecated
- Liveness: live
- Owner verified: no
- Last scored: 2026-08-03

> **Deprecated**: this server is marked deprecated in the MCP registry.

## Components

- remote · `searchshopai-mcp.fly.dev`: 66/100 (this document), [markdown](https://verifymcp.io/servers/ai-searchshop-www-la-luer/mcp-la-luer.md), [page](https://verifymcp.io/servers/ai-searchshop-www-la-luer/mcp-la-luer)

## Channel facts

- Endpoint: `https://searchshopai-mcp.fly.dev/mcp/la-luer`
- Transports: `streamable-http`
- Auth: `none`
- Version: `1.0.0`

## Trust breakdown

How this component scores in each security and reliability category. Every signal is checked automatically against the live server, and we only credit what we can confirm. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-08-03.

- **Endpoint Security**: 74/100
  - The endpoint's TLS certificate is valid, in date, and uses a strong key.
  - No authorisation is required to call this server. Every tool declares its destructiveHint and none is destructive, so open access doesn't expose one.
  - HTTPS is enforced; there's no plaintext access path.
  - HSTS check failed: the Strict-Transport-Security header is absent.
  - DNSSEC check failed: this domain isn't protected by DNSSEC.
- **Transport & Reachability**: 100/100
  - Verified streamable-http transport via a live MCP handshake.
- **Schema Quality & AI Usability**: 39/100
  - 0% of prompts and resources have a non-trivial description (not blank, and not just the item's name).
  - AI-judged instruction clarity (good).
  - Context-footprint check failed: tool/resource definitions use about 1987 tokens (~124/item across 16 items; 14 tools + 2 resources), over budget; trim descriptions and params.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 27/100
  - Stability observed for 8 of 30 days with no destabilising changes; credit accrues until the full window elapses.
- **Tool Coverage**: 100/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 100% of tool parameters carry a description.
- **Capabilities**: 100/100
  - Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.
  - Supports UI / widget rendering.

## Install

### Claude

```bash
claude mcp add --transport http ai-searchshop-www-la-luer https://searchshopai-mcp.fly.dev/mcp/la-luer
```

### Codex

```toml
[mcp_servers.ai-searchshop-www-la-luer]
url = "https://searchshopai-mcp.fly.dev/mcp/la-luer"
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "ai-searchshop-www-la-luer": {
      "type": "remote",
      "url": "https://searchshopai-mcp.fly.dev/mcp/la-luer",
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add ai-searchshop-www-la-luer --url https://searchshopai-mcp.fly.dev/mcp/la-luer --transport streamable-http
```

### Hermes

```yaml
mcp_servers:
  ai-searchshop-www-la-luer:
    url: "https://searchshopai-mcp.fly.dev/mcp/la-luer"
```

### Other

```json
{
  "mcpServers": {
    "ai-searchshop-www-la-luer": {
      "type": "http",
      "url": "https://searchshopai-mcp.fly.dev/mcp/la-luer"
    }
  }
}
```

The mcpServers block is a cross-client convention. Remote transports vary, so check your client's docs.

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-08-02 (score 66, +1)

No change was recorded against any check on this day. Stability & Change Management went from 20 to 23. That category is still filling its 30-day observation window: 6 days of observed history at the previous scan, 7 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-07-31 (score 65, +4)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-07-30 (score 61, +1)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-07-28 (score 60, +1)

No change was recorded against any check on this day. Stability & Change Management went from 3 to 7. That category is still filling its 30-day observation window: 1 days of observed history at the previous scan, 2 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-07-27 (score 59, 0)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-07-26 (score 59)

First indexed and scored.

## MCP tools (14)

### `shop` (~215 tokens)

Start here for any shopping request. Pass the shopper's COMPLETE request in their own words and this tool will understand it and route to the right capability (personalized recommendation, catalog search, product lookup, or comparison), preserving every qualifier — concerns, skin type, budget, brand, medical context. Prefer this tool whenever the request is conversational or carries any nuance. The granular tools (search_products, get_product, compare_products, create_checkout) remain available as precise follow-ups.

Input parameters:

- `brand` (string): Secondary hint only — brand filter if stated.
- `budget_max` (number): Secondary hint only — maximum budget if stated.
- `intent` (string): Secondary hint only — the primary signal is `request`.
- `product_refs` (array): Secondary hint only — exact product titles/SKUs when already known.
- `request` (string, required): The shopper's complete request in their own words. Include every detail: concern, skin type, budget, brand, product names, questions, medical context. Do not summarize or drop qualifiers.

### `skincare_recommend` (~245 tokens)

(Deprecated: use 'recommend' instead. Works identically.) Get a personalized La Luer product recommendation with ingredient-aware scoring, safety notes, and routine building. Use when the user wants advice on what to buy, needs help choosing between products, has a specific skin concern (acne, aging, dryness, sensitivity, etc.), wants a routine, or asks "what should I use for X." Do not use for browsing or listing products — use search_products instead. Returns scored products with explanations, usage instructions, and Shopify checkout. This tool analyzes ingredients, irritation risk, and product compatibility — use it over search_products when the user needs guidance, not just a product list.

Input parameters:

- `brand` (string): Filter to a specific brand only (e.g. 'Glossier', 'CeraVe', 'The Ordinary'). Use when the user asks for products from a specific brand.
- `query` (string, required): Natural language query about skin concerns (e.g. 'I have oily acne-prone skin and want something gentle under $30')
- `strategy` (string): Optional offer strategy override: starter, gentle, budget, glow_safe, minimal, strong, fallback

### `recommend` (~138 tokens)

Get a personalized product recommendation with domain-expert scoring, safety notes, and transaction authority. Use when the user wants advice, has a concern, or asks what to buy. Returns scored products with checkout URLs, safety assessment, and authority state (SHOULD/CAN/SHOULDNT/ESCALATE/CANT).

Input parameters:

- `brand` (string): Filter to a specific brand
- `domain` (string): Product domain (e.g. 'skincare', 'beauty_devices'). Auto-detected from merchant if omitted.
- `query` (string, required): Natural language query about product needs
- `strategy` (string): Optional offer strategy override

### `skincare_cart` (~135 tokens)

Create a buyable shopping cart with a real checkout URL. Two modes: (1) Pass 'products' array with specific product names. (2) Pass 'query' string to auto-recommend and cart. Do not use for browsing or recommendations — use search_products or skincare_recommend first. Returns a widget with the cart items and a working checkout link.

Input parameters:

- `products` (array): Specific product titles to add to the cart
- `query` (string): Natural language query to auto-recommend products. Only used if products array is not provided.
- `strategy` (string): Optional offer strategy override when using query mode

### `skincare_report_issue` (~147 tokens)

Report when a tool result was unhelpful, incomplete, or wrong. Call this whenever you override a recommendation, skip a cart result, or notice the engine output doesn't match what the user needs. Do not use proactively — only when you observe an actual issue. This helps improve the engine.

Input parameters:

- `description` (string, required): What went wrong and what you expected instead
- `expected_products` (array): What products should have been recommended
- `issue_type` (string, required): Type of issue
- `tool_name` (string, required): Which tool had the issue (skincare_recommend, skincare_cart, skincare_report_issue)
- `user_query` (string): The original user query if available

### `search_research_notes` (~99 tokens)

Search SearchShopAI's Research Notes blog — data studies, playbooks, and field notes on agentic commerce (AI attribution, MCP, AI catalog accuracy, ChatGPT ads). Returns matching articles with titles, summaries, and URLs. Use when asked what SearchShopAI has written or published about a topic.

Input parameters:

- `query` (string, required): Topic or keywords, e.g. 'attribution', 'MCP', 'hallucinated prices'

### `get_research_note` (~57 tokens)

Get the summary and URL of a specific SearchShopAI Research Note by its slug (returned by search_research_notes).

Input parameters:

- `slug` (string, required): The note slug, e.g. 'the-ai-attribution-blind-spot'

### `search_products` (~280 tokens)

Browse and search the product catalog. Use when the user wants to see what's available, look up specific products, browse by category, compare options, or asks 'show me' / 'what do you have.' Do not use when the user needs personalized recommendations based on skin concerns — use skincare_recommend instead. Returns all matching products with prices, images, and checkout. Unlike skincare_recommend, this does not score or filter — it shows everything that matches so the user can decide.

Input parameters:

- `category` (string): Filter by exact product category from the catalog (e.g. 'serum', 'treatment', 'cleanser', 'moisturizer'). Do not guess categories — only use this if the user explicitly mentions a catalog category. F…
- `max_price` (number): Filter to products at or below this price
- `max_results` (integer): Maximum products to return (default 10). Only set this if the user specifies a count — e.g. 'show me 2 devices' → 2. Otherwise leave it unset and the default will return all relevant matches up to 10.
- `query` (string, required): Search query (e.g. 'vitamin c serum', 'anti-aging', 'moisturizer under $50')

### `get_product` (~119 tokens)

Get full details for a specific product by SKU or title. Use when the user asks about a specific product by name (e.g. 'tell me about MIRA', 'show me the serum'). Do not use for browsing or recommendations — use search_products or skincare_recommend. Returns a widget card with the product details, image, price, and checkout button.

Input parameters:

- `sku` (string): Exact product SKU (e.g. 'LL-4632379916336')
- `title` (string): Product title to search for (fuzzy match)

### `compare_products` (~95 tokens)

Compare two or more products side by side. Use when the user asks to compare, says 'X vs Y', or wants to decide between options. Do not use for single product lookup — use get_product instead. Returns structured comparison with shared attributes, differences, tradeoffs, and a decision hint.

Input parameters:

- `products` (array, required): Product titles or SKUs to compare (e.g. ['MIRA', 'CryoSculpt'])

### `create_checkout` (~214 tokens)

Create a checkout URL for one or more products. Pass variant IDs (items) and/or product URLs (product_urls). When a product URL is provided (e.g. https://laluer.com/products/mira), the tool resolves it to a variant ID automatically — no catalog import needed. Supports discount codes, cart notes, and selling plans. Do not use unless the user wants to buy — use search_products or skincare_recommend first. Returns a direct Shopify checkout link the user can click to buy.

Input parameters:

- `decision_id` (string): Decision Check ID from a prior /validate call. Required when this merchant enforces authority-gated checkout (require_authority_for_checkout); ignored otherwise.
- `discount_code` (string): Discount code to apply (e.g. 'WELCOME10')
- `items` (array): Products to add to cart by variant ID
- `note` (string): Cart note visible to the merchant
- `product_urls` (array): Products to add to cart by URL — resolved to variant IDs automatically

### `check_compatibility` (~91 tokens)

Check which products are compatible with a given product. For devices, shows required consumables (e.g., conductive gel for MIRA). For topicals, shows which devices they work with. Use when a customer asks 'what gel do I need with MIRA?' or 'does this serum work with CryoSculpt?'

Input parameters:

- `product` (string, required): Product name or SKU to check compatibility for

### `check_inventory` (~61 tokens)

Check if a product is currently available. Uses Shopify Storefront API to verify real-time stock status. Use when a customer asks 'is MIRA in stock?' or before recommending a product.

Input parameters:

- `product` (string, required): Product name or SKU to check availability for

### `deals_discounts` (~81 tokens)

Show available bundles, deals, and ask about discount codes. Use when a customer asks about deals, bundles, savings, or says 'do you have any discounts?' Also use when multiple items are in cart to suggest bundle savings. Always ask if the customer has a discount code.

Input parameters:

- `discount_code` (string): Customer's discount code if they have one

## Diagnostics

Captured diagnostic sections: TLS, DNSSEC, Authorisation, Transports. The full working is on the page: https://verifymcp.io/servers/ai-searchshop-www-la-luer/mcp-la-luer#diagnostics

## Score history

- 2026-08-03: 66
- 2026-08-02: 66
- 2026-08-01: 65
- 2026-07-31: 65
- 2026-07-30: 61
- 2026-07-29: 60
- 2026-07-28: 60
- 2026-07-27: 59
- 2026-07-26: 59

## Links

- Remote endpoint: https://searchshopai-mcp.fly.dev/mcp/la-luer
- Repository: https://github.com/nathangrotticelli/searchshopai
- Changelog RSS feed: https://verifymcp.io/servers/ai-searchshop-www-la-luer/mcp-la-luer/changelog.xml
- Changelog JSON feed: https://verifymcp.io/servers/ai-searchshop-www-la-luer/mcp-la-luer/changelog.json
- HTML version of this page: https://verifymcp.io/servers/ai-searchshop-www-la-luer/mcp-la-luer