Discovery
Free — no payment required.catalog_overview
The shape of the catalog: unique products, listings, brands, categories, retailers, price observations, and when it was last updated.
“What’s in the Syntalic catalog?” “How many products and retailers do you actually cover?”
coverage_map
Where the catalog is deep vs. thin, as priced product counts and a quality status per retailer × country × category. The one to check before spending.
“Do you have good coverage of grocery in Canada?” “Which categories are thin on Best Buy?”
browse_categories
The product category tree with per-node product counts. Pass a parent path to drill into a subtree.
“What categories do you cover?” “Show me what’s under Home & Kitchen.”
list_retailers
Retailers in the catalog with product counts, countries covered, and freshness.
“Which retailers do you cover in Canada?” “How fresh is your Costco data?”
list_brands
Brands in the catalog with product counts. An optional query prefix-matches the name, so “sam” finds Samsung.
“Do you have Anker products?” “List the vacuum brands you track.”
Shopper
Per-query price: $0.01best_price
Find the cheapest current price for a product across covered retailers.
“What’s the cheapest place to buy AirPods Pro right now?” “Find me the best price for a Dyson V15 in Canada.”
price_history
Show price trends over time for a specific product.
“How has the Sony WH-1000XM5 changed in price over the last 90 days?” “Has the Dyson V15 ever been cheaper than $549?”
deal_finder
List products currently below their typical price in a category.
“Show me the best deals on espresso machines this week.” “What’s on sale in cordless vacuums under $400?”
price_drop_alert
Surface products whose prices dropped recently.
“Which TVs have dropped in price in the last 7 days?” “Any recent price drops on Bose headphones?”
Marketing
Per-query price: $0.01competitive_landscape
Per-retailer pricing snapshot for a category or competitor set.
“How do AirPods Pro prices compare across Amazon, Walmart, and Best Buy?” “Show me the competitive landscape for robot vacuums under $500.”
brand_tracker
All products from a brand with current price + availability.
“Track all Bose headphone listings in the US.” “What KitchenAid stand mixers are currently in stock and what do they cost?”
promo_intelligence
Promotional activity by retailer or brand — who’s running deals, how deep, how often.
“What promotions has Walmart been running on KitchenAid this quarter?” “How aggressive are Amazon’s promos on Apple accessories vs. Best Buy’s?”
share_of_shelf
Percentage of category listings that each brand occupies — a digital-shelf-share signal.
“What’s Apple’s share of shelf in wireless earbuds?” “Which brand dominates listings in the cordless drill category?”
price_positioning
Premium / mid / value positioning by brand within a category.
“Where does Anker sit in wireless charging — premium or value?” “Show me the price positioning of all major brands in robot vacuums.”
Analyst
Per-query price: $0.02inflation_tracker
Period-over-period price change for a category.
“What’s the inflation rate for grocery essentials in the US over the last 6 months?” “How much have TV prices changed year-over-year?”
price_dispersion
Spread of prices for a single product across retailers.
“How much price variance is there for the iPhone 16 Pro across US retailers?” “Which products in the laptop category have the widest price spread?”
retailer_index
Average pricing posture of a retailer relative to a category baseline.
“Is Costco actually cheaper than Walmart on average for grocery items?” “Where does Target sit on the price index for home goods?”
category_summary
Statistical pricing summary for a category — distribution, median, range.
“Give me a pricing summary for cordless vacuums under $500.” “What’s the price distribution for noise-cancelling headphones?”
Taxonomy
Per-query price: $0.01 These resolve product identity against GS1 GPC, the global standard for what a product is, independently of how any one retailer files it. Use them when you need a stable category key across retailers rather than a browse path. All three are built to make misses visible: an unresolved input comes back explicitly unresolved rather than quietly guessing at a neighbouring category.classify_product_type
Resolve a product type or phrase to its GS1 GPC brick, with the brick’s class, family, and segment.
“What’s the GPC brick for olive oil?” “Classify ‘cordless drill’ and ‘air fryer’ into GPC.”
gpc_reverse_lookup
The crosswalk in reverse: given GPC codes, return the retailer browse nodes mapped to them. Returns a total count alongside the list, so truncation is detectable rather than silent.
“Which browse nodes map to GPC brick 10000045?” “Show me every category that maps to the olive oil brick.”
gpc_brick_attributes
The GS1 attribute schema for one or more bricks — the attribute names and permitted values GS1 defines for that category.
“What attributes does GS1 define for coffee?” “What values are allowed for the ‘Packaging Type’ attribute on protein bars?”
Utility
Free — no payment required.wallet_info
Show the MCP’s wallet addresses, balance per chain, and funding instructions.
“What’s my Syntalic wallet balance and where do I send USDC?”
Filters
The Shopper, Marketing, and Analyst tools accept these optional filters. You don’t pass them directly — the MCP infers them from your prompt (“in Canada”, “on Amazon”, “last 30 days”):
The Taxonomy tools take GPC codes or product phrases instead, and the Discovery tools take their own filters —
coverage_map, for example, narrows by country, platform, category, or quality status.
Sample response
Abest_price call for “wireless earbuds” returns something like: