BUY-2924: US Launch LinkedIn Posts
Status: Draft Channel: BuyWhere LinkedIn Company Page Goal: Drive US developer awareness and API signups Campaign: US Launch April 2026
Post 1: US Launch Announcement
Timing: Week 1, Day 1
UTM: ?utm_source=linkedin&utm_medium=social&utm_campaign=us-launch-apr26-p1
Body:
Big news for US developers: BuyWhere is now live in the United States.
We've opened our agent-native product catalog API to US developers — giving you access to 600K+ Amazon US products through a single, AI-friendly API.
Why this matters for AI agents:
✅ Structured JSON-LD responses LLMs parse without custom instructions ✅ MCP server for zero-config tool registration in Claude Desktop, Cursor, or any MCP-compatible agent ✅ Real-time prices across Amazon US, Walmart, Target, and Best Buy ✅ Built-in confidence scores and availability signals ✅ Affiliate-tracked purchase links via Amazon Associates
Whether you're building a price tracker, deal finder, or full shopping agent — your users deserve better than scraped data that breaks.
Free API access: api.buywhere.ai
What's the hardest part about getting live product data into your AI agent? Genuinely curious what the US dev community is running into.
#AI #ShoppingAgent #DeveloperTools #APIFirst #MCP
Post 2: The Problem with AI Shopping Agents
Timing: Week 1, Day 3
UTM: ?utm_source=linkedin&utm_medium=social&utm_campaign=us-launch-apr26-p2
Body:
Most "AI shopping agents" have a dirty secret: they're running on top of fragile scrapers that break every time the e-commerce platform changes their HTML.
Here's what that looks like in practice:
❌ Anti-bot blockers that kill your scraper mid-run ❌ Price data that's stale by the time you get it ❌ Inconsistent product schemas across 10 different stores ❌ Hours of infrastructure work instead of building actual intelligence
We spent 3 years building the data layer so your agent doesn't have to.
BuyWhere gives AI agents a clean product catalog API with: → 600K+ Amazon US products → Real-time prices from Walmart, Target, Best Buy → Schema.org JSON-LD format (LLMs were trained on this) → MCP tools for zero-config agent integration
The future of commerce isn't a chatbot that pretends to shop. It's an agent that can actually check live prices and give you an affiliate link.
Docs: api.buywhere.ai/docs
#AI #ShoppingAgent #MCP #DeveloperTools
Post 3: MCP Integration Demo
Timing: Week 2
UTM: ?utm_source=linkedin&utm_medium=social&utm_campaign=us-launch-apr26-p3
Body:
Want your Claude agent to search Amazon US products? Here's what that looks like with BuyWhere MCP:
User: "Find me running shoes under $150 on Amazon"
Agent calls:
search_products(
query="running shoes",
platform="amazon_us",
max_price=150,
limit=10
)
→ Returns 10 ranked results with prices,
ratings, review counts, and affiliate links
That's it. No scrapers. No custom parsers. Just a tool call.
We built 7 MCP tools for AI shopping agents: • search_products • price_comparison • batch_lookup • bulk_compare • explore • best_price • compare_matrix
All support region=us or platform=amazon_us to scope results to Amazon US.
Install: pip install buywhere-mcp
Docs: api.buywhere.ai/docs/guides/mcp
#MCP #Claude #AI #ShoppingAgent #DeveloperTools
Post 4: Use Case — Deal Alert Bot
Timing: Week 3
UTM: ?utm_source=linkedin&utm_medium=social&utm_campaign=us-launch-apr26-p4
Body:
Here's what you can build with BuyWhere: a deal alert agent that watches Amazon US for price drops.
Real example:
Category: Electronics
Min discount: 30%
Current run: 47 products with 30%+ off
Top deal:
Sony WH-1000XM5 Headphones
Was: $399.99 → Now: $279.99 (30% off)
Rating: 4.7/5 (12,430 reviews)
Affiliate link: [tracked]
That's an affiliate link with commission — Amazon Associates pays out for qualifying purchases through BuyWhere-tracked links.
Commission rates: • Electronics: 3% • Home & Kitchen: 4.5% • Beauty: 4.5% • Luxury Beauty: 10%
If you're building a deal-finding product, price tracker, or shopping assistant — affiliate integration is built in.
Get started: api.buywhere.ai
#AI #ShoppingAgent #AffiliateMarketing #Deals #Amazon
Post 5: Why US Developers Should Care
Timing: Week 4
UTM: ?utm_source=linkedin&utm_medium=social&utm_campaign=us-launch-apr26-p5
Body:
US developers: if you're building anything that involves product recommendations, price comparison, or shopping assistance with AI — there's a better way to get product data.
The old approach: → Scrape Amazon, Walmart, Target → Fight anti-bots → Maintain 4 different parsers → Hope nothing breaks
The BuyWhere approach: → One API call → 600K+ normalized products → Schema.org JSON-LD that LLMs already understand → MCP tool registration in 2 lines of config
We're not trying to replace your agent's intelligence. We're giving it a clean data layer so you can focus on the reasoning, not the scraping.
Coverage: Amazon US, Walmart, Target, Best Buy, and growing.
Free tier: 1,000 requests/day Pro tier: 50,000 requests/day
Start free: api.buywhere.ai
What would you build if product data was just... solved?
#AI #DeveloperTools #ShoppingAgent #APIFirst #Tech
Performance Tracking
| Post | Impressions | Engagements | CTR | US Signups |
|---|---|---|---|---|
| P1 | ||||
| P2 | ||||
| P3 | ||||
| P4 | ||||
| P5 |
UTM Parameter: utm_source=linkedin&utm_medium=social&utm_campaign=us-launch-apr26