DealsPing MCP Server

India's AI-powered deals discovery platform. Find the best deals on Amazon, Flipkart and more Indian stores via Claude and other AI platforms.

MCP Server URL

https://dealsping-ai.akhilbabumfwa.workers.dev/mcp

Transport: Streamable HTTP (JSON-RPC 2.0 over POST, optional SSE stream over GET).

Available Tools

Tool	Description
search_deals	Search deals by keyword
get_best_deals	Get top ranked deals
get_latest_deals	Get newest deals
get_trending_deals	Get trending deals
get_deals_by_category	Filter by category
get_deals_by_price	Filter by price range
get_deals_by_store	Filter by store
get_deal	Get specific deal details
get_categories	List all categories
check_and_link	Check product & get affiliate link
bulk_check_and_link	Check multiple products
search_catalog	Search product catalog

Usage

Add to Claude: Settings → Connectors → Add custom connector → https://dealsping-ai.akhilbabumfwa.workers.dev/mcp

About DealsPing

DealsPing (dealsping.in) aggregates the best deals from Amazon, Flipkart, Myntra, Ajio and more Indian e-commerce stores.

As an Amazon Associate, DealsPing earns from qualifying purchases.

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Architecture

Cloudflare Workers + D1 backend that mirrors DealsPing's Firebase deal data into a fast, AI-queryable API, MCP server, and admin dashboard. Completely separate from dealsping-next — read-only against Firebase, never writes back.

• sync.js — pulls deals + monitored_deals from Firestore REST API (no SDK), maps to D1 schema, upserts, marks stale deals inactive.
• engine.js — deal score (0-100) calculation, freshness decay, AI list rebuilding, 4-day category rotation.
• api.js — public REST API (/api/*), rate-limited, CORS-open, 5-minute cache headers.
• mcp.js — MCP server at /mcp (Streamable HTTP: JSON-RPC 2.0 handshake, tools/list, tools/call).
• admin.js — protected dashboard API (/admin/*), gated by X-Admin-Secret header.
• index.js — router + cron handler (sync every 6h, rebuild lists every 2d, rotate categories every 4d).

Setup

npm install

# 1. Create the D1 database
npx wrangler d1 create dealsping-ai-db
# → copy the returned database_id into wrangler.toml

# 2. Apply schema (local + remote)
npx wrangler d1 execute dealsping-ai-db --file=schema.sql
npx wrangler d1 execute dealsping-ai-db --file=schema.sql --remote

# 3. Set secrets
npx wrangler secret put FIREBASE_API_KEY   # your Firebase Web API key
npx wrangler secret put SYNC_SECRET        # random string
npx wrangler secret put ADMIN_SECRET       # random string

# 4. Deploy
npx wrangler deploy

Endpoints

Path	Purpose
GET /health	Health check
GET /api/deals/best	Top deals by score
GET /api/deals/latest	Newest deals
GET /api/deals/trending	Trending deals
GET /api/deals/featured	Featured deals
GET /api/deals/search?q=	Keyword search
GET /api/deals/category/:category	Deals by category
GET /api/deals/price?min=&max=	Deals by price range
GET /api/deals/store/:store	Deals by store
GET /api/deals/:id	Single deal (id or slug)
GET /api/lists/:list_type	Any AI list
GET /api/categories	Category counts
GET /api/catalog/stats	ASIN catalog stats
GET /api/stats	Platform stats
GET/POST/DELETE /mcp	MCP server (Streamable HTTP)
GET /.well-known/mcp.json	Lightweight discovery manifest
GET /.well-known/ai-plugin.json	ChatGPT plugin manifest
GET /openapi.yaml	OpenAPI 3.0 spec
GET /dashboard	Admin dashboard UI
GET/POST /admin/*	Admin API (needs X-Admin-Secret)
POST /sync	Manual sync trigger (needs X-Sync-Secret)

AI Lists

best_deals, latest_deals, trending_deals, featured_deals, under_500, under_1000, under_2000, under_5000, electronics, fashion, home_kitchen, mobiles, with_coupon, with_bank_offer, amazon_deals, flipkart_deals.

Deal Score Formula (0-100)

discount_score   = (discount_pct / 100) * 25
freshness_score  = freshness (0-1, decays over 7 days) * 20
price_score      = tiered by current_price, max 15
trending_score   = 15 if trending else 0
featured_score   = 10 if featured else 0
coupon_bonus     = 10 if coupon_code else 0
bank_offer_bonus = 5 if bank_offer else 0

Notes / Limitations

• Rate limiting (60 req/min/IP) is best-effort in-memory per Worker isolate — not strictly distributed. Sufficient to blunt casual abuse; for hard guarantees, migrate to Durable Objects or a KV-backed counter.
• Affiliate URLs are copied verbatim from Firebase — never modified.
• Sync never touches Firebase; it's read-only via the Firestore REST API with an API key.
• firestore.rules on the source project already have allow read: if true on deals/monitored_deals, so the API key alone is sufficient (no service account needed for reads).
• The ASIN catalog (asin_catalog table, powering check_and_link/search_catalog) intentionally stores no price/image/availability data — see check_and_link's tool description for why.

License

MIT

Contact

akhilbabumfwa@gmail.com