io.github.akhilbabumfwa-oss/dealsping-ai is an MCP server that find the best deals on Amazon, Flipkart and more Indian e-commerce stores via AI. Its tool list has not been published yet over http, requires no API key, and scores 52/100 on MCPpedia's security, maintenance and efficiency rubric.
Config is the same across clients - only the file and path differ.
{
"mcpServers": {
"io-github-akhilbabumfwa-oss-dealsping-ai": {
"args": [
"-y",
"wrangler"
],
"command": "npx"
}
}
}Are you the author?
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Find the best deals on Amazon, Flipkart and more Indian e-commerce stores via AI.
This server supports HTTP transport. Be the first to test it - help the community know if it works.
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Wrangler affected by OS Command Injection in `wrangler pages deploy`
**Summary** A command injection vulnerability (CWE-78) has been found to exist in the `wrangler pages deploy` command. The issue occurs because the `--commit-hash` parameter is passed directly to a shell command without proper validation or sanitization, allowing an attacker with control of `--commit-hash` to execute arbitrary commands on the system running Wrangler. **Root cause** The `commitHash` variable, derived from user input via the `--commit-hash` CLI argument, is interpolated directl
Arbitrary remote code execution within `wrangler dev` Workers sandbox
### Impact The V8 inspector intentionally allows arbitrary code execution within the Workers sandbox for debugging. `wrangler dev` would previously start an inspector server listening on all network interfaces. This would allow an attacker on the local network to connect to the inspector and run arbitrary code. Additionally, the inspector server did not validate `Origin`/`Host` headers, granting an attacker that can trick any user on the local network into opening a malicious website the ability
Arbitrary remote file read in Wrangler dev server
### Impact Sending specially crafted HTTP requests and inspector messages to Wrangler's dev server could result in any file on the user's computer being accessible over the local network. An attacker that could trick any user on the local network into opening a malicious website could also read any file. ### Patches This issue was fixed in `wrangler@3.19.0`. Wrangler will now only serve files that are part of your bundle, or referenced by your bundle's source maps. ### Workarounds Configure Wr
Cloudflare Wrangler directory traversal vulnerability
### Impact The Wrangler command line tool (<=wrangler@3.1.0 or <=wrangler@2.20.1) was affected by a directory traversal vulnerability when running a local development server for Pages (wrangler pages dev command). This vulnerability enabled an attacker in the same network as the victim to connect to the local development server and access the victim's files present outside of the directory for the development server. ### Patches Wrangler2: Upgrade to v2.20.1 or higher. Wrangler3: Upgrade to v3
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India's AI-powered deals discovery platform. Find the best deals on Amazon, Flipkart and more Indian stores via Claude and other AI platforms.
https://dealsping-ai.akhilbabumfwa.workers.dev/mcp
Transport: Streamable HTTP (JSON-RPC 2.0 over POST, optional SSE stream over GET).
| 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 |
Add to Claude: Settings → Connectors → Add custom connector →
https://dealsping-ai.akhilbabumfwa.workers.dev/mcp
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.
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.
deals + monitored_deals from Firestore REST API (no SDK), maps to D1 schema, upserts, marks stale deals inactive./api/*), rate-limited, CORS-open, 5-minute cache headers./mcp (Streamable HTTP: JSON-RPC 2.0 handshake, tools/list, tools/call)./admin/*), gated by X-Admin-Secret header.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
| 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) |
best_deals, latest_deals, trending_deals, featured_deals, under_500, under_1000, under_2000, `und