retailerapi
About
Unified product data across major US retailers (Walmart, Amazon, eBay, Target, Best Buy, Lowe's, Home Depot): lookups, price history, sellers, reviews.
Details
- Author
- retailerapi
- Categories
- Other, Web Scraping
Jump to
Setup
Install retailerapi in your MCP client (Claude Desktop, Cursor, Windsurf, and others).
Repository: https://github.com/retailerapi/mcp
Follow the installation instructions in the repository README, then restart your MCP client.
Model Context Protocol server forretailerapi.com— a unified product-data API covering major US retailers. Two tools your AI agent can call directly: product lookups and live offers.
Works withClaude Desktop,Claude Code,Cursor, and any other MCP-compatible client over stdio.
Covered retailers: Walmart, Amazon, eBay, Target, Best Buy, Lowe's, Home Depot. Setinclude_cross_retailer=trueon a product lookup to surface cached cells for every retailer we have for that UPC.
Editclaude_desktop_config.json(macOS:~/Library/Application Support/Claude/claude_desktop_config.json, Windows:%APPDATA%\Claude\claude_desktop_config.json) and add:
{ "mcpServers": { "retailerapi": { "command": "npx", "args": ["-y", "@retailerapi/mcp"], "env": { "RETAILERAPI_KEY": "rk_live_your_key_here" } } } }
Restart Claude Desktop. The retailerapi tools will appear in the tool picker.
claude mcp add retailerapi npx -y @retailerapi/mcp \ --env RETAILERAPI_KEY=rk_live_your_key_here
Add to~/.cursor/mcp.json(or the project-level.cursor/mcp.json):
{ "mcpServers": { "retailerapi": { "command": "npx", "args": ["-y", "@retailerapi/mcp"], "env": { "RETAILERAPI_KEY": "rk_live_your_key_here" } } } }
RETAILERAPI_KEY=rk_live_your_key_here npx @retailerapi/mcp
The process speaks MCP over stdio (newline-delimited JSON-RPC on stdin/stdout). Logs go to stderr.
Resolve any identifier (UPC / EAN / ISBN / GTIN / Amazon ASIN / retaileritem_id) into a normalized product summary.Base call (1 token)returns: title, brand, image, current price, identifiers, weight, dimensions, MSRP, description, categories, full price history, aggregated stats,retailer_links(free 'where to find it'),Bucket-1 facts(sold_tag, estimated_sales, is_best_seller, pack_count, hazmat), andcomputed marketplace fees(referral_fee_usd, wfs_fee_usd). Fees are FREE in base call — Keepa parity.
Setinclude_cross_retailer=trueto add thecross_retailerblock — a map keyed by retailer slug of cached per-retailer cells (price, in_stock, Bucket-1 fields) for every retailer we have for this UPC (+2 tokens). Read-only over our cache. Setinclude_seller_context=trueto add live seller-side state (is_restricted, WFS eligibility) on marketplace retailers (+3 tokens).
To force a fresh scrape of a specific retailer (bypassing cache), call withretailer=<slug>andforce_refresh=true. This is the only way to force fresh data from the API.
Barcode lookups also return a diagnostic_metablock with the source retailer for each top-level field (includingweight_lbs_sourceanddimensions_source— useful when one retailer's catalog is missing physical specs and another retailer backfills them) and adata_quality_score(0.0–1.0).
Package vs assembled.Retailers that distinguish boxed-for-shipping weight from product weight populateweight_assembled_lbs+weight_package_lbs(and paralleldimensions_assembled+dimensions_package). Top-levelweight_lbs/dimensionsare the derived "best available" — assembled wins, package fills in, plain weight is the last resort. Retailers exposing only one weight populateweight_lbsand leave the explicit pair asnull.
- "Look up UPC 045496590161 — what's the brand, price, and Walmart referral fee?"
- "Find UPC 194629116676 across every retailer — who has it cheapest?"
- "What's the WFS fee on this product? Are there any seller restrictions on Amazon?"
List current marketplace sellers on a product, including price, in-stock state, and which seller owns the buy box.
Example prompt:"Who has the buy box on item 1689065034 and what's the next-cheapest seller?"
Tool calls return structured JSON errors instead of crashing the agent:
pnpm install pnpm --filter @retailerapi/mcp build RETAILERAPI_KEY=rk_live_… node packages/mcp/dist/index.js
The MCP Inspector (npx @modelcontextprotocol/inspector) is the easiest way to exercise the tools manually.
An MCP server that connects AI agents to Amazon product, search, and review data across 20 marketplaces via the ChocoData Amazon Scraper API.
Shopify store analysis, product catalog extraction, pricing strategy, and inventory monitoring
AI-powered e-commerce research via MCP — search Amazon, Alibaba & AliExpress for winning products, vet suppliers, calculate FBA margins. 19 tools.
MCP360 is a unified gateway and marketplace that provides 100+ external tools and custom MCPs through a single integration for AI agents.
Quantitative research, backtesting, creator-marketplace subscriptions, editable strategy forks, continuous copy trading, and controlled brokerage workflows through more than 120 MCP tools.
Real-time product data from Amazon, eBay, Walmart, Kaufland and many others — directly inside your AI assistant
Hosted MCP server for Amazon sellers using Claude, ChatGPT, and other AI clients.
Collective intelligence for AI shopping agents — 23 MCP tools for buyer intelligence, seller analytics, price alerts, and trend tracking.
Connect Amazon Seller Central to Claude or ChatGPT via Two Minute Reports MCP and get accurate insights on orders, sales, inventory, and revenue performance.
Sign in to leave a review
Use Google, GitHub, or an email account so ratings stay tied to real people.
No reviews posted yet.




