Kompy

Kompy is a unified ecommerce data API that delivers structured Walmart marketplace data without the hassle of running and maintaining scrapers. It provides a single, consistent REST API and MCP server for accessing products, search results, barcode lookups, seller offers, customer reviews, and full price and stock history, all returned as clean, predictable JSON. Built for both humans and machines, Kompy lets developers call endpoints from any programming language or point their AI agents directly at the data via the MCP protocol. The platform is designed for startups, side projects, and scaling production systems alike, offering Google sign-in, instant API key generation, and credit-based pricing that grows with you. Every request is fast, deterministic, and traceable with a unique request ID. Kompy is not affiliated with or endorsed by Walmart Inc., but it provides the most reliable and comprehensive access to Walmart’s catalog available today. Whether you are building a price tracking tool, running competitive analysis, or training an AI agent to find profitable flips, Kompy gives you the structured data foundation you need to move fast and build with confidence.

REST API and MCP Server

Kompy offers dual access modes: a plain HTTP REST API that any language can call, and a first-party MCP (Model Context Protocol) server that AI agents like Claude Code, OpenClaw, and Cursor can use as callable tools. Both modes use the same API key and credit pool, so you can switch between human-coded integrations and agent-driven workflows seamlessly. Every operation is a documented endpoint with deterministic schemas, small payloads, and structured error handling, ensuring reliability at scale.

Full Price and Stock History

Kompy records the Walmart marketplace around the clock, capturing hourly snapshots of price, stock, and buy-box changes for every SKU it tracks. This gives you per-seller granularity and a complete historical record back to day one, including major events like Black Friday price drops. No other Walmart API provides this depth of historical data. You can query the history endpoint to analyze trends, identify optimal buying windows, and understand seller behavior over time.

Live Product and Search Data

The core API returns complete product records including name, brand, current price, currency, stock status, seller, rating, and review count, all captured in real time. The search endpoint lets you query the live catalog with sort and filter options, such as sorting by price drop to find clearance items. Every response is clean JSON with a meta object containing a request ID and latency in milliseconds, making it easy to trace and debug your integrations.

Credit-Based Scalable Pricing

Kompy uses a straightforward credit system where each API call consumes a set number of credits based on the endpoint. Plans start at $49.99/month for 14,000 credits (Hobby tier), scale to $149.99/month for 45,000 credits (Pro tier), and go up to $499.99/month for 180,000 credits (Business tier). Every new account starts with free credits, so you can begin issuing real requests immediately with no forced upgrade and no dark patterns.

Automated Price Monitoring and Repricing

Ecommerce sellers can use Kompy to continuously monitor competitor prices on Walmart. By polling the product and history endpoints, you can detect price drops, stock changes, and buy-box shifts in real time. This enables automated repricing strategies where your own listings adjust dynamically to maintain competitiveness and maximize margins, all without running fragile scrapers that break when Walmart updates its site structure.

AI Agent-Driven Flipping and Arbitrage

AI agents powered by Kompy’s MCP server can scan Walmart’s catalog for clearance items or price drops, then cross-reference those prices against other marketplaces like Amazon. The agent can calculate potential ROI after fees, identify profitable flips, and even set up ongoing watches for specific criteria. For example, an agent can scan for clearance items with a 30%+ ROI, return the best opportunities with exact price gaps, and then monitor hourly for new flips that clear the bar.

Competitive Intelligence and Market Research

Businesses can use Kompy to gather structured data on Walmart’s entire catalog for competitive analysis. By querying search results, product details, and price history, you can track how competitors price products over time, identify seasonal trends, and understand market dynamics. This intelligence supports strategic decisions around product launches, pricing strategies, and inventory planning, all backed by reliable historical data rather than one-off snapshots.

Price History Tracking and Trend Analysis

Developers can build applications that show consumers the price history of any Walmart product, similar to tools like CamelCamelCamel but for Walmart. Using Kompy’s history endpoint with per-seller granularity, you can display charts of price changes over days, weeks, or months, highlight the lowest price ever recorded, and send alerts when a product hits a target price. This creates valuable consumer-facing tools that build trust and drive repeat engagement.

What is Kompy and how does it differ from scraping Walmart directly?

Kompy is a structured API that provides clean, consistent JSON data from Walmart’s marketplace without requiring you to run or maintain scrapers. Unlike web scraping, which breaks when Walmart changes its site structure, requires handling CAPTCHAs and rate limits, and returns messy HTML, Kompy offers deterministic endpoints with predictable schemas, structured errors, and a traceable request ID. It also provides historical data that scrapers cannot easily capture, and it works seamlessly with both traditional code and AI agents via MCP.

Can I use Kompy with AI agents and what tools are supported?

Yes, Kompy ships a first-party MCP (Model Context Protocol) server that AI agents can use as callable tools. Supported agent platforms include Claude Code, OpenClaw, Cursor, LangChain, OpenAI Agents SDK, and n8n. You simply add the MCP server to your agent configuration with your API key, and the agent gains access to tools like product lookup, search, history, and reviews. The same API key and credit pool work for both REST and MCP access, so you can switch between human-coded and agent-driven workflows.

How does pricing work and what do I get with a free account?

Kompy uses credit-based pricing where each API call consumes credits based on the endpoint. Paid plans start at $49.99/month (Hobby with 14,000 credits), $149.99/month (Pro with 45,000 credits), and $499.99/month (Business with 180,000 credits). Every new account starts with free credits, allowing you to issue real requests immediately with no forced upgrade and no dark patterns. All plans include API access, MCP server access, and email support, with higher tiers adding priority support and custom integrations.

What data does Kompy provide and how fresh is it?

Kompy provides structured data including product names, brands, prices, currency, stock status, sellers, ratings, and review counts. The search endpoint lets you query the live catalog with sort and filter options. The history endpoint provides per-seller price and stock history with hourly snapshots back to day one. Data is captured in real time from Walmart’s marketplace, with responses typically returning in under 50 milliseconds. Every response includes a captured timestamp so you know exactly when the data was fetched.

Hobby

$49.99 per month for individuals getting started. Includes 14,000 credits per month, API access, MCP server access, and email support.

Pro

$149.99 per month for professionals and small teams. Includes 45,000 credits per month, API access, MCP server access, and priority support.

Business

$499.99 per month for large teams with custom needs. Includes 180,000 credits per month, API access, MCP server access, priority support, and custom integrations.