Kompy

Kompy is a unified, enterprise-grade API platform that delivers structured Walmart marketplace data without the operational overhead of running and maintaining scrapers. It provides a single, cohesive interface for accessing products, search results, barcode lookups, seller offers, customer reviews, and comprehensive price and stock history. All data is returned as clean, consistent JSON, eliminating the need for complex parsing or data cleaning pipelines. The platform is designed for both human developers and autonomous AI agents. It offers a traditional REST API that can be consumed from any programming language, and a first-party Model Context Protocol (MCP) server that allows AI agents to query Walmart data directly as callable tools. This dual-access approach ensures maximum flexibility, whether you are building a custom application in Python, Node.js, or Go, or integrating with agent frameworks like Claude Code, OpenClaw, Cursor, LangChain, or the OpenAI Agents SDK. Kompy is purpose-built for businesses and professionals who need reliable, real-time ecommerce data to drive pricing strategies, competitive analysis, inventory management, and arbitrage opportunities. With Google sign-in, instant API key generation, and a transparent credit-based pricing model, Kompy scales seamlessly from a side project to a full production environment. The platform records marketplace data around the clock, providing historical price and stock snapshots per seller back to day one, a capability unmatched by other Walmart APIs. This historical depth, combined with millisecond response times and deterministic schemas, makes Kompy an essential tool for data-driven decision-making in ecommerce.

Unified REST API and MCP Server

Kompy provides a dual-access architecture that allows you to interact with Walmart data through either a traditional REST API or a native MCP server. The REST API offers deterministic, documented endpoints that return predictable JSON shapes, making it easy to integrate from any programming language or framework. The MCP server exposes the exact same operations as callable tools for AI agents, enabling autonomous workflows. This unified approach means you use the same API key and credit system regardless of how you access the data, significantly reducing integration complexity and maintenance overhead.

Full Historical Price and Stock Data

Kompy records the Walmart marketplace around the clock, capturing price, stock, and buy-box changes for every tracked SKU. This feature provides per-seller granularity with hourly snapshots, going back to the first day a product was tracked. Unlike other Walmart APIs that only offer current data, Kompy gives you a complete historical record. This allows for sophisticated trend analysis, identification of pricing patterns, and data-driven forecasting. The historical data is accessible through a dedicated endpoint that returns clean, structured JSON, making it easy to analyze price movements over time.

Comprehensive Product and Search Endpoints

The platform offers a full suite of data endpoints covering the entire Walmart catalog. The product endpoint returns a complete product record including name, brand, current price, stock status, seller information, rating, and review count. The search endpoint allows you to query the live catalog with sorting and filtering capabilities, returning results in milliseconds. Additionally, Kompy provides a barcode lookup endpoint for scanning products by UPC or EAN, and a reviews endpoint that delivers customer feedback and ratings. Each response includes a unique request ID for tracing and debugging, ensuring full auditability.

Real-Time Data with Millisecond Latency

Every API request to Kompy is processed with enterprise-grade performance, returning responses in under 50 milliseconds in most cases. The platform maintains a constantly updated cache of the Walmart marketplace, ensuring that you always receive the most current prices, stock levels, and seller information. This real-time capability is critical for time-sensitive applications such as dynamic pricing, inventory arbitrage, and competitive monitoring. The low latency also enables high-frequency polling and automated agent workflows without degrading performance or incurring excessive costs.

Automated Price Arbitrage and Flipping

Ecommerce entrepreneurs and resellers can use Kompy to automatically scan Walmart clearance items and identify products with significant price gaps compared to other marketplaces like Amazon. By leveraging the search endpoint with price drop sorting and the history endpoint for trend analysis, users can quickly find items with a 30% or higher ROI potential. The real-time data and historical context allow for informed buying decisions, while the MCP server enables autonomous agents to continuously monitor for new opportunities and alert users when profitable flips appear.

Competitive Price Monitoring and Dynamic Pricing

Retailers and ecommerce managers can integrate Kompy into their pricing engines to track competitor prices on Walmart in real time. The API provides per-seller price and stock data, allowing businesses to adjust their own pricing strategies dynamically. The historical price data enables analysis of competitor pricing patterns, seasonal trends, and promotional cycles. This intelligence helps businesses optimize their margins, maintain competitive positioning, and automate price adjustments based on market conditions, all without the need for fragile web scraping infrastructure.

AI-Powered Market Research and Analysis

Data scientists and AI researchers can feed Kompy's structured data into machine learning models for market analysis, demand forecasting, and consumer behavior studies. The clean JSON output and consistent schemas simplify data ingestion pipelines, while the historical records provide rich training datasets. AI agents equipped with Kompy's MCP tools can autonomously gather product intelligence, identify emerging trends, and generate actionable business insights. This use case is particularly valuable for hedge funds, investment firms, and consulting agencies analyzing retail market dynamics.

Inventory and Supply Chain Optimization

Supply chain managers and procurement teams can use Kompy to monitor stock levels and seller availability across the Walmart marketplace. The real-time stock data helps identify potential supply shortages or overstock situations, enabling proactive inventory management. The per-seller granularity allows businesses to track which third-party sellers are offering specific products, facilitating vendor evaluation and negotiation. Combined with historical data, this feature supports long-term supply chain planning and risk assessment by revealing supplier reliability and stock volatility patterns.

What is Kompy and how does it differ from web scraping?

Kompy is a professional API that provides structured Walmart marketplace data without the need for web scraping. Unlike scrapers, which are fragile, require constant maintenance, and can be blocked by anti-bot measures, Kompy offers a reliable, documented REST API and MCP server that return clean JSON data. It handles all the complexity of data extraction, parsing, and normalization, delivering consistent results with millisecond latency. This eliminates the operational burden of managing proxies, handling CAPTCHAs, and maintaining parsing logic, allowing you to focus on building your application or analysis.

How does the credit-based pricing system work?

Kompy operates on a transparent credit-based pricing model. Each API request consumes a certain number of credits based on the endpoint and data volume. You purchase a monthly plan that includes a fixed number of credits, and you can upgrade or downgrade at any time. All accounts start with free credits upon signup, allowing you to test the API without any upfront commitment. There are no hidden fees, no forced upgrades, and credits roll over or expire according to your plan terms. The system is designed to scale from small side projects to large production environments without any disruption.

Can I use Kompy with AI agents and automation tools?

Yes, Kompy is specifically built for AI agent integration. It provides a first-party MCP server that exposes all API operations as callable tools for agents. This means you can connect Kompy directly to Claude Code, OpenClaw, Cursor, LangChain, OpenAI Agents SDK, n8n, or any other framework that supports MCP or plain HTTP. Your agents can then autonomously search products, retrieve historical data, check prices, and gather reviews. The same API key works for both REST and MCP access, simplifying your infrastructure.

What data does Kompy provide and how current is it?

Kompy provides comprehensive Walmart marketplace data including product details (name, brand, price, rating, reviews), search results, barcode lookup information, seller offers, and full price and stock history. All current data is real-time, captured from the live Walmart marketplace with millisecond response times. Historical data includes hourly snapshots with per-seller granularity, going back to the first day a product was tracked. This combination of real-time and historical data is unique among Walmart APIs and enables deep trend analysis and informed decision-making.