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Glama
AleWWH1104

Skincare Recommendation MCP Server

by AleWWH1104

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault

No arguments

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{
  "listChanged": false
}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
search_productsA

Search the store's product catalog by skin type and/or skincare concern.

Args: skin_type: e.g. "grasa", "seca", "mixta", "sensible", "normal". Empty to skip this filter. concern: e.g. "acné", "manchas", "arrugas", "sensibilidad", "hidratación". Empty to skip this filter. in_stock_only: only return products currently in stock.

get_product_detailsA

Get full details (price, stock, active ingredients) for one product by its id.

find_alternativesA

Find other in-stock products sharing at least one active ingredient with the given product - useful when it's out of stock or the client wants a different brand with the same effect.

check_ingredient_conflictsA

Check whether a candidate product's active ingredients conflict with ingredients the client already uses.

Args: current_ingredients: active ingredients in the client's current routine. candidate_ingredients: active ingredients of the product being considered.

recommend_productsA

End-to-end recommendation: find in-stock products matching the client's skin type and concerns, and flag any that conflict with their current routine.

Args: skin_type: client's skin type, e.g. "grasa". concerns: concerns to address, e.g. ["acné", "manchas"]. current_ingredients: active ingredients already in the client's routine.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

A4.2/5.0

Scored across 5 tools

Disambiguation4/5

Most tools map to clearly distinct tasks: catalog search, product details, alternatives, conflict checking, and full recommendations. The only notable ambiguity is between search_products and recommend_products, since the latter includes the former's filtering behavior plus conflict flagging, but the descriptions make the distinction recoverable.

Naming Consistency5/5

All tool names follow a consistent verb_noun snake_case pattern: search_products, get_product_details, find_alternatives, check_ingredient_conflicts, recommend_products. No mixed naming conventions or vague verbs.

Tool Count5/5

Five tools is a well-scoped size for a specialized skincare recommendation server. Each tool addresses a distinct step in the workflow without redundancy or bloat.

Completeness5/5

The tool surface covers the full recommendation workflow: searching/filtering, retrieving details, finding alternatives, checking ingredient conflicts, and generating end-to-end recommendations. No obvious dead ends or missing operations for the stated purpose.

Maintenance

ActivityMaintained
ResponsivenessNo issues