ANIME INTELLIGENCE / AI PURCHASE INTELLIGENCE
by anime-intelligence.goodmy0312.workers.dev in Developer tools
AI commerce intelligence for anime, industrial parts, replacements, sourcing and agent buying.
https://anime-intelligence.goodmy0312.workers.dev/mcp
Last 30 days
- Uptime
- 100%
- Response time
- 151 ms typical, 151 ms slowest 5%
- Last check
- 3 h ago
- Next check
- in 2 h
How to call it
Add it to any MCP client that supports remote servers.
{
"mcpServers": {
"anime-intelligence-ai-purchase-intelligence": {
"type": "http",
"url": "https://anime-intelligence.goodmy0312.workers.dev/mcp"
}
}
}20 tools
- search_anime_product
FREE candidate discovery for physical Japanese anime collectibles. Use when the user wants options or when the agent needs to inspect alternatives before paying. Handles vague and multilingual queries, but do NOT stop here when the user asks for value, rarity, authenticity, BUY/W
- identify_anime_product
Multilingual vague-to-canonical shopping intelligence for physical anime collectibles. Accept requests such as 'I want a ONE PIECE figure', 'a big cheap Pikachu plush', 'é¨å±ã«é£¾ãããã£ãããã¾ã', or 'a Japan-only Luffy figure' even when the exact product is unknow
- anime_market
Identity-matched market intelligence for Japanese anime collectibles. Resolve the exact product first, then compare supported Japan and global marketplace observations while rejecting likely wrong editions and name collisions. Returns low/median/high asking prices, offer count, f
- anime_rarity
Estimate scarcity and rerelease/replenishment risk for the exact Japanese collectible, not just the franchise. Combines matched supply, price premium, release age and limited-edition signals so an agent can avoid paying a false rarity premium. WHEN TO USE: Use before paying a sca
- anime_authenticity
Pre-purchase counterfeit and listing-risk screening for Japanese anime collectibles. Cross-checks canonical identity, official references, price relationships and matched listing signals to flag bootleg risk, suspiciously cheap offers and identity mismatches. WHEN TO USE: Use whe
- anime_buy_wait
Turn Japanese collectible data into an actionable BUY, WAIT, WATCH or AVOID decision. Uses identity-matched price, availability, scarcity, rerelease/replenishment risk and authenticity signals so an agent can act instead of assembling several searches manually. WHEN TO USE: Use w
- best_place
Return the best current purchase route for an exact Japanese anime collectible. Compares identity-matched seller offers, price, availability, marketplace and freshness so an autonomous agent can move from product identification to a concrete seller route. WHEN TO USE: Use when th
- listing_match
Verify whether a seller listing matches the exact Japanese anime collectible, edition or variant. Uses canonical identity, JAN/model evidence and stored marketplace match signals to detect wrong-version and name-collision risk. WHEN TO USE: Use immediately before purchase when th
- purchase_deadline
Purchase-window intelligence for Japanese anime collectibles. Returns stored verified preorder, lottery, reservation or sales deadlines when available, with remaining time and a separate release schedule so agents do not confuse release dates with order cutoffs. WHEN TO USE: Use
- landed_cost
Destination-aware purchase cost for Japanese anime collectibles. Supports Japan buyers explicitly and cross-border buyers conservatively, returning known item/shipping totals and refusing to invent unavailable duty, tax or brokerage amounts. WHEN TO USE: Use when an agent is read
- price_history
Stored asking-price history for the exact Japanese anime collectible across supported marketplaces. Returns 7/30/90/180-day ranges, daily medians, current percentile and trend without claiming completed-sale history. WHEN TO USE: Use before BUY/WAIT when the agent needs 7/30/90/1
- full_intelligence
One paid call for an end-to-end Japanese anime collectible purchase decision. Resolves the exact edition, returns identity-matched Japan/global market intelligence, price history, listing-match evidence, purchase deadlines, destination-aware landed-cost context including Japan bu
- shopping_intelligence
Agent-neutral structured shopping intelligence. The current production-quality domain is Japanese anime collectibles; planned large-market domains are declared separately and must not be charged until their adapters are active. WHEN TO USE: Use as the preferred endpoint when an A
- record_purchase_intent
Record that an AI agent selected a product or merchant as a purchase candidate. Use after shopping_intelligence when the agent has chosen an offer and is preparing to hand off or execute the purchase.
- travel_shopping_intelligence
Search and rank travel inventory for AI agents. Use for hotels/accommodations now; car rentals are supported when Booking.com Demand credentials are configured. Attractions and transfers use provider beta endpoints. Returns a recommended option, alternatives, price signals and a
- travel_provider_status
Check whether the Booking.com Demand travel adapter is configured and which travel verticals are available.
- commerce_search
Search consumer electronics, automotive parts, enterprise procurement, MRO and electronic components. Automotive/B2B recommendations require exact OE/MPN/part identity.
- parts_search
Free search of the PARTS INTELLIGENCE catalog for discontinued parts, replacement parts, industrial components, appliance/service parts, camera/audio/tool/IT parts and other exact model-number items.
- parts_intelligence
Paid exact-part intelligence for lifecycle status, discontinuation, verified successor/substitute relationships, official documents and sourcing. Compatibility is never inferred from title similarity alone. Price: 0.05 USDC via x402.
- parts_status
Read the current PARTS INTELLIGENCE catalog and public-source ingest pipeline status.
Security scan
- No findings. We scan names, descriptions and tool definitions for hidden instructions and other prompt-injection patterns.
Recent checks
| When | Result | HTTP | Time |
|---|---|---|---|
| 3 h ago | Passed | 200 | 151 ms |