Kompy

Kompy is the premier, enterprise-grade data API for the Walmart marketplace, engineered to deliver structured, actionable intelligence without the operational burden of running and maintaining web scrapers. It provides a single, unified interface for accessing the entire Walmart catalog, returning clean, consistent JSON for products, search results, barcode lookups, seller offers, customer reviews, and comprehensive price and stock history. This platform is meticulously designed for a sophisticated audience: developers building scalable ecommerce applications, data analysts requiring reliable market intelligence, and AI agents needing direct, real-time access to retail data. The core value proposition is eliminating the fragility, latency, and maintenance overhead of traditional scraping. Kompy offers a dual-access architecture, allowing human developers to interact via a powerful REST API from any programming language, while AI agents and automation frameworks can connect directly through a first-party MCP server. This ensures that whether you are coding a complex pricing engine or deploying an autonomous trading agent, you receive the same high-fidelity data. With features like hourly snapshots, per-seller granularity, and a full historical record back to day one, Kompy positions itself as the definitive source for Walmart marketplace data. It is built for those who demand reliability and speed, offering instant API keys via Google sign-in and a transparent, credit-based pricing model that scales effortlessly from a side project to a high-volume production environment. Kompy is not merely a tool; it is a strategic asset for gaining a competitive edge in the dynamic world of online retail.

Unified REST API and MCP Server

Kompy provides a dual-access architecture that caters to both human developers and autonomous AI agents. The REST API offers a standard, documented HTTP interface with predictable JSON schemas, allowing integration from any language like Python, Node.js, or Go without requiring an SDK. Simultaneously, the first-party MCP server exposes the exact same operations as callable tools for AI agents, enabling seamless integration with platforms like Claude Code, OpenClaw, and Cursor. This ensures that your entire stack, from manual scripts to sophisticated agent workflows, accesses the same high-quality data with a single API key.

Comprehensive Historical Data

Kompy records the Walmart marketplace around the clock, capturing hourly snapshots of price, stock, and buy-box changes for every tracked SKU. This feature provides the full price history per seller, back to day one, offering an unparalleled depth of market intelligence. No other Walmart API maintains this level of granular historical data. This allows users to perform sophisticated trend analysis, identify optimal pricing windows, and make data-driven decisions based on months of accumulated data, such as tracking a product from a $389 Black Friday price to a $447.99 current price.

Deterministic and Structured Data Outputs

Every API request returns clean, consistent, and deterministic JSON. The schemas are predictable, payloads are small and efficient, and errors are structured for easy handling. This eliminates the chaos and parsing challenges associated with scraped HTML. A single product request returns a complete record including ID, name, brand, price, currency, stock status, rating, review count, seller name, and a precise capture timestamp. Each response also includes a unique request_id for full traceability, ensuring that your data pipeline remains robust and reliable.

Full Catalog Coverage and Search Capabilities

Kompy provides access to the entire Walmart catalog, enabling users to query live inventory with powerful search and filter capabilities. The search endpoint allows for sorting and filtering results, such as finding clearance items sorted by price drop. This feature is complemented by dedicated endpoints for barcode lookup, seller offers, and customer reviews, providing a holistic view of any product's market position. Whether you need to find a specific product by ID or scan for arbitrage opportunities across the entire marketplace, Kompy delivers the necessary tools with millisecond latency.

Automated Retail Arbitrage

Savvy resellers can leverage Kompy to scan the Walmart catalog for clearance and discounted items, then instantly compare those prices against other marketplaces like Amazon. By using the search and history endpoints, users can identify products with a significant price gap and a proven history of price stability. The system can even be configured to provide real-time alerts when a new flip clears a specific ROI bar, such as a 30% margin, enabling automated, data-driven purchasing decisions that maximize profit.

Competitive Price Monitoring and Dynamic Pricing

Ecommerce businesses can use Kompy to continuously track competitor pricing on Walmart. By monitoring the price and stock history of key SKUs, companies can implement dynamic pricing strategies. The hourly snapshots and per-seller granularity allow for precise adjustments, ensuring a business remains competitive without leaving money on the table. This use case is critical for retailers who need to respond in real-time to market shifts and maintain optimal margins across their product lines.

AI-Powered Market Analysis and Agent Workflows

Data scientists and AI developers can integrate Kompy directly into their agent workflows using the MCP server. An AI agent can be given a tool to query the Walmart catalog, analyze price history, and make autonomous recommendations. For example, an agent can be tasked with scanning for high-demand products with a recent price drop and a strong seller rating, then compile a report or even execute a simulated trade. This enables a new class of intelligent, data-driven automation for market analysis.

Product Research and Validation for Sellers

Entrepreneurs looking to launch new products on Walmart can use Kompy for deep market research. By analyzing historical pricing, stock levels, and customer reviews for competing products, they can validate demand, identify market gaps, and set competitive entry prices. The ability to pull full product records and review data with a single API call streamlines the due diligence process, allowing for faster, more informed go-to-market strategies.

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

Kompy is a structured data API for the Walmart marketplace that provides clean, consistent JSON data without the need for web scraping. Unlike scraping, which is fragile, slow, and requires constant maintenance to handle website changes, Kompy offers a stable, documented, and high-performance interface. It returns deterministic data with millisecond latency, includes historical records, and provides a single API key for access via REST or MCP, making it significantly more reliable and efficient for production use.

How do I get started with the Kompy API?

Getting started is designed to be fast and frictionless. You sign in with your Google account, and you are instantly issued an API key. The platform includes a generous allocation of free credits for initial testing. You can then start making requests to the REST API using any HTTP client or configure your AI agent to connect via the MCP server. The process from sign-in to your first successful response typically takes about 14 seconds.

What data is included in a product response?

A single product request returns a comprehensive record. The JSON response includes the product's Walmart ID, name, brand, current price, currency, stock availability, average customer rating, total review count, the seller's name, and a timestamp of when the data was captured. This provides a complete snapshot of the product's current market status. Additional endpoints are available for detailed search results, full price history, and individual customer reviews.

How does the credit-based pricing work?

Kompy operates on a transparent, credit-based pricing model. Each API request consumes a certain number of credits, which are allocated monthly based on your chosen plan (Hobby, Pro, or Business). Credits are used for all operations, including product lookups, searches, and history requests. This model allows you to scale your usage from a small side project to a high-volume production environment simply by upgrading your plan. There are no hidden fees, and every account starts with free credits to evaluate the service.