This was a lot of fun to build as a team - learning a TON about MCPs making them Anthropic approved "connectors"... We'll be making this way more user friendly and when approved by @AnthropicAI will be called "Shopping".

Huge day for us. After 6 months of building, testing, breaking, rebuilding, and figuring out way more MCP/OAuth chaos than I ever wanted to know… LemmeBuyIt MCP is officially live across every major MCP registry. I know a lot of my friends and family probably see me post about data, APIs, product search, AI agents, and have no clue what I’m actually building half the time. 😂 The simple version: We built a way for AI agents like Claude, OpenAI, and other MCP-compatible tools to search real products across 86 major US retailers with 262M products indexed. Walmart, Target, Home Depot, Best Buy, Nordstrom, Zappos, Sephora, and a lot more. Your AI can now ask things like: “Find this product across retailers.” “Compare prices.” “Show me price history.” “Check if this barcode is in stock.” “Pull Amazon ASIN and Buy Box history.” And it can actually get structured retail data back. No scraping. No messy API setup. Just connect and go. This has been a grind. Late nights, early mornings, vacation coding, weekend debugging, and a whole lot of why the hell is this not working? But today, it’s live. Really proud of what we shipped. If you’re building anything with AI agents, ecommerce, Amazon FBA, retail data, or product search, check it out: lemmebuyit.com

After 6 months of building, LemmeBuyIt MCP is live across every major, Model Context Protocol registry. What that means: Anyone using Claude (or any MCP-compatible AI agent) can now connect to real-time product search across 86 US retailers, Walmart, Target, Home Depot, Best Buy, Nordstrom, Zappos, Sephora, and more, with 262M products indexed. In one prompt, your AI can: 🔆 Compare prices on the same item across multiple retailers 🔆 Track price history (up to 2 years of weekly samples) 🔆 Pull Amazon ASIN price Buy Box history alongside cross-retailer data 🔆 Find in-stock SKUs by barcode  Connect with one click of OAuth, no API keys to manage.  Live on: • Official MCP Registry - registry.modelcontextprotoco…                   • Smithery - smithery.ai/servers/lemmebuy… • Glama - glama.ai/mcp/connectors/com.… • mcp.so - mcp.so/server/lemmebuyit/Lem… Direct install in Claude Desktop: mcp.lemmebuyit.com/mcp
 Built with Cloudflare Workers, OAuth 2.1 PKCE, Streamable HTTP transport. Free tier for product search lookup, paid tier unlocks weekly / monthly / yearly price history. If you're building with Claude, OpenAI, or any MCP-compatible AI agent and want shopping / retail data, try it out.

 Head to lemmebuyit.com and get started today!!  #MCP #ClaudeAI #AI #ProductSearch #Ecommerce #AmazonFBA #OpenAI #Anthropic #LLM

One of the most interesting parts of launching the MCP server hasn't been the technology. It's seeing what people build once they get access to the data. We've seen users building shopping agents, gift finders, comparison shopping tools, sourcing workflows, reseller assistants, inventory lookups, and niche community bots that would've required months of custom integrations just a year ago. The common theme isn't AI. It's access. Once an agent can search real products, compare retailers, validate pricing, and pull live product data, the ideas start showing up fast. Honestly, I think we're still in the first inning of what people are going to build with product intelligence and MCP. #MCP #AgenticAI #AIAgents #ArtificialIntelligence #Ecommerce #ProductIntelligence #DeveloperTools #RetailTech #OpenAI #Claude #Anthropic #AmazonFBA

For years, AI could write code, analyze documents, and answer questions. But when it came to shopping, it was mostly guessing. That changes when AI gets access to real products, real pricing, real inventory, and real retailer data. The next generation of AI agents won't just answer questions. They'll help make decisions. #AgenticAI #ArtificialIntelligence #MCP #Ecommerce #RetailTech #ProductIntelligence #AIAgents #Claude #OpenAI #Anthropic #Cursor

We just shipped the LemmeBuyIt MCP Free tier. 50,000 free requests/month. Real product data from 50 retailers, Walmart, Target, Home Depot, Best Buy, Zappos, Macy’s, REI, and more. No credit card, no trial. What it does: Lets any AI agent (Claude, Cursor, Goose, custom GPTs, etc.) search and look up real products across retailers via the Model Context Protocol. No scraping, no proxy stack, no per-store integration work. Real use cases we’re already seeing: → Personal shopping agents: “Find me a winter coat under $200 with great reviews” → Gift-finder workflows for niche audiences → Custom shopping assistants for hobby communities → Comparison shopping that actually compares → Restocking automations (school supplies, gym gear, household basics) For builders: drop it into your MCP client of choice in under a minute. Works anywhere MCP runs. For shoppers: AI assistants can finally help with shopping in a way that doesn’t suck. Free tier covers shopping data. Standard and Pro plans unlock Amazon resale intelligence and price history for power users. Try it: lemmebuyit.com/sign-up #MCP #AI #Shopping #Claude #IndieHackers

Just shipped: LemmeBuyIt MCP Free tier. 50,000 free requests/month. Real product data from 50 retailers. Plug it into Claude, Cursor, Goose, or any MCP client, no card, no trial, no catch. Go build something weird with AI shopping. lemmebuyit.com #amazonfba

This week I was sitting on the beach while my infrastructure kept moving. Retailers refreshed. Pipelines ran. Code got written. Then my phone buzzed. Not because something broke. Because my AI had already investigated the issue, built a fix, and was waiting for approval. That's a weird feeling. The breakthrough isn't teaching AI how to code. It's teaching it when to ask for help. #ArtificialIntelligence #AgenticAI #SoftwareEngineering #DataEngineering #Automation #DeveloperTools #BuildInPublic

Everybody wants pricing data. Very few people ask whether the pricing can actually be trusted. After connecting hundreds of millions of products across retailers and marketplaces, I've learned the hardest problem isn't collecting data. It's proving the data is telling the truth. That's where product intelligence gets interesting. #AmazonFBA #AmazonSeller #Ecommerce #ProductIntelligence #DataEngineering

The biggest problem in ecommerce isn’t lack of data. It’s that a massive amount of the data is wrong. Stale inventory. Dead listings. Bad mappings. Multipacks using the same UPCs. Conflicting prices across marketplaces. At small scale, bad data is annoying. At large scale, it becomes infrastructure debt. #AmazonFBA #AmazonSeller #OnlineArbitrage #RetailArbitrage #Ecommerce #ProductIntelligence #DataEngineering #AI #BuildInPublic #SaaS

513,704 products refreshed in the last hour.... No proxies. No games. Just data. LemmeBuyIt isn’t guessing. We’re pulling live pricing and inventory straight from the source. 430,598 in stock 83,106 out of stock Across brands like Nike, Puma, Columbia Sportswear, and more... This isn’t scraped junk. This is clean, normalized, real-time product intelligence at scale. While everyone else is throttled, blocked, or paying for garbage datasets… we’re refreshing half a million products like it’s nothing. And this is just the beginning. Live pricing changes everything. #LemmeBuyIt #ProductData #Ecommerce #RetailData #AmazonFBA #WalmartSeller #DataEngineering #OpenClaw #Arbitrage #APIs

The biggest change this week wasn’t speed. It was that we stopped double-checking everything. No more refreshing. No more second guessing. No more “is this still accurate?” Just run it and act. That’s when a system stops being something you verify… and starts being something you trust. #ArtificialIntelligence #AI #SaaS #Automation #BuildInPublic #DataInfrastructure #Ecommerce #OnlineArbitrage #RetailArbitrage #AmazonSeller #WalmartSeller #Reselling

Most systems don’t fail because they lack data. They fail because they’re always behind it. By the time you see it, it’s already changed, and that gap is where bad decisions happen. We spent the last few weeks closing that gap. Live data. Multiple execution paths. Systems that actually hold under pressure. Now it’s not about pulling information. It’s about acting on it before it changes. That’s the shift. And it applies way beyond ecommerce. Every industry has the same problem, data that’s just a little too late. We’re building systems that don’t fall behind it. #ArtificialIntelligence #AI #SaaS #Startups #Tech #Innovation #AIInfrastructure #Automation #SoftwareEngineering #BuildInPublic #DataInfrastructure #Ecommerce #OnlineArbitrage #RetailArbitrage #AmazonSeller #WalmartSeller #Reselling #EcommerceBusiness

A big part of this breakthrough was building a headless browser layer that can actually operate in environments where standard requests fall apart. A lot of pipelines break the second systems like Akamai and PerimeterX come into play. Instead of forcing it, we built our own headless browser path that behaves like a real user, runs only when needed, and feeds clean data back into the system. That’s what unlocked consistent live pricing at scale.

Live data isn’t a feature anymore, it’s the entire game. Everyone talks about AI like it’s magic… But garbage in = garbage out. If your data is stale, delayed, or scraped once and forgotten… your “AI” is just guessing with confidence. The teams winning right now are plugged into live data feeds: Real-time pricing Inventory that actually exists Signals that move when the market moves This isn’t about dashboards. It’s about decision velocity. The difference between reacting tomorrow vs right now? That’s margin. That’s conversions. That’s growth. Static data is dead. Live data is leverage. Get access today @ LemMeBuyIt.com #AmazonSeller #WalmartSeller #AmazonFBA #WalmartMarketplace #DynamicPricing #LiveData #RetailData #InventoryManagement #BuyBox #ListingOptimization #EcommerceGrowth #ProfitMargins

Claude went down yesterday and a lot of people were completely stuck. Messages started rolling in, workflows broken, tools not responding, everything paused waiting for it to come back. We didn’t really feel it. Not because it didn’t happen, but because nothing in our setup depends on one model. Fix was simple. Add multiple LLMs, use slash commands, switch when one falls over. Same workflow, different model, keep moving. That’s the difference. If your system stops when one model goes down, you don’t have a system, you have a dependency. @MiniMax_AI continues to be the most stable default for us. Everything else is situational. Most people are still picking models. We’re building systems that don’t depend on them. #ArtificialIntelligence #AI #MachineLearning #SaaS #Startups #Tech #Innovation #AIInfrastructure #LLM #Automation #SoftwareEngineering #BuildInPublic #Founders #ProductDevelopment #DataInfrastructure

Most people are still prompting LLMs. Rewrite this Analyze that Try again It works… until you need consistency. We started using skill sets instead. Same tasks Same intent 
Same process every time And everything changed. Less randomness Less re-explaining Way more consistency across models Claude, Codex, doesn’t matter. The workflow stays the same. That’s when it clicks: You don’t need better prompts. You need a better way of working. #Agentic #AI #LLM #Automation #Engineering #Startup #Claude #Codex #Amazon #Ecom #Affiliate #Marketing

We use elastic with 1TB of ecommerce data - we’ll look into this with @LinkScopic @Lemmebuyit_

For a while, everything in our system was treated the same. Same checks.
 Same priority.
 Same effort. It felt right… until we scaled. Then it became obvious: We were spending time in the wrong places. High-value items were waiting.
 Low-value items were getting equal attention.
 And we were burning resources on things that didn’t matter. So we changed one thing: 👉 not everything gets treated equally anymore Now the system decides: * what gets checked first * what gets checked more often * and what’s not worth the effort Everything got faster.
 Cheaper.
 More predictable. Scale isn’t about doing more. It’s about deciding what’s worth doing. #BuildInPublic #DataInfrastructure #SaaS #Automation #StartupBuilding #Engineering #AIInfrastructure #AgenticAI #Affiliate #Marketing