Kompy

Kompy is a sophisticated, unified API platform that provides structured, real-time data from the Walmart marketplace without the complexity and fragility of operating custom web scrapers. It delivers a comprehensive suite of data endpoints covering products, search results, barcode lookups, seller offers, customer reviews, and full price and stock history, all returned as clean, consistent JSON payloads. Designed for both human developers and autonomous AI agents, Kompy offers a dual interface: a standard REST API accessible from any programming language, and a first-class MCP (Model Context Protocol) server that enables AI agents such as Claude Code, OpenClaw, and Cursor to query Walmart data directly as callable tools. The platform is built for reliability, speed, and scalability, with deterministic schemas, small payloads, structured error handling, and sub-50 millisecond response times on most queries. Kompy records the marketplace around the clock, capturing hourly snapshots of price, stock, and buy-box changes for every tracked SKU, preserving the entire price history per seller back to day one. This historical depth is a unique differentiator, as no other Walmart API offers such granular, persistent data. The service is positioned for a broad audience: individual developers building side projects, professional teams integrating ecommerce data into applications, and large organizations requiring custom integrations. Authentication is streamlined with Google sign-in and instant API key generation, and the credit-based pricing model scales gracefully from hobbyist exploration to production-level demands. Kompy is not affiliated with or endorsed by Walmart Inc., but it provides an indispensable bridge to the Walmart ecosystem for anyone needing reliable, structured marketplace intelligence.

Unified REST and MCP Interface

Kompy provides a dual-access architecture that accommodates both traditional software development and modern AI agent workflows. The REST API exposes every operation as a documented HTTP endpoint, callable from any language such as Python, Node.js, Go, or curl, with predictable JSON shapes and structured error responses. Simultaneously, the same operations are available through a first-party MCP server, allowing AI agents to discover and invoke them as native tools. This unified approach means a single API key grants access to both interfaces, enabling seamless integration across human-coded applications and autonomous agent systems without duplicating infrastructure or credentials.

Comprehensive Walmart Data Coverage

The platform aggregates a full spectrum of Walmart marketplace data into a single, coherent API. Developers can retrieve complete product records including name, brand, price, currency, stock status, rating, review count, and seller information with a single request. Search functionality allows querying the live catalog with sorting and filtering capabilities. Barcode lookup provides instant product identification. Seller offers are surfaced with detailed pricing and availability. Customer reviews and ratings are accessible for any product. This breadth eliminates the need to orchestrate multiple data sources or maintain separate scraping pipelines, centralizing all Walmart data needs into one consistent service.

Historical Price and Stock Tracking

Kompy distinguishes itself by recording the marketplace continuously, capturing hourly snapshots of price, stock, and buy-box changes for every SKU it tracks. The full Walmart price history, broken down per seller, is preserved back to the platform's inception, offering an unparalleled longitudinal dataset. Users can query historical data for any product over custom date ranges, such as the last 30 days or 12 months, and visualize trends like Black Friday price drops or seasonal fluctuations. This historical depth is critical for price optimization, competitive analysis, and identifying profitable resale opportunities, and it is a capability that no other Walmart API provides.

High Performance and Developer Experience

Every API response is engineered for speed and clarity, with typical latencies under 50 milliseconds for product lookups and search queries. Responses include a unique request_id for tracing and debugging, along with metadata such as latency metrics. The JSON schemas are minimal and deterministic, reducing parsing complexity and payload size. Authentication is simplified through Google sign-in and instant API key generation, eliminating lengthy onboarding processes. The platform also provides an OpenAPI specification for automated client generation, comprehensive documentation, and a price history tracker tool. This focus on developer experience ensures that users can go from sign-up to their first successful API call in approximately 14 seconds.

Competitive Price Monitoring and Dynamic Repricing

Ecommerce businesses and resellers can leverage Kompy to continuously monitor Walmart prices for their product catalog, receiving real-time updates on price changes, stock availability, and seller offers. The historical price data enables analysis of pricing trends, identification of optimal pricing windows, and detection of competitor strategies. By integrating the API into a pricing engine, businesses can automate repricing decisions to maintain competitiveness or maximize margins. For example, a reseller can set up a workflow that alerts them when a product's price drops below a threshold, allowing them to purchase inventory at the lowest possible cost before prices rebound.

AI-Powered Arbitrage and Flipping Opportunities

The MCP server integration makes Kompy exceptionally powerful for AI agents tasked with identifying profitable arbitrage opportunities. An agent can search for clearance or discounted items on Walmart, retrieve their full price history, and cross-reference with Amazon or other marketplaces to calculate potential return on investment. As demonstrated in the platform's examples, an agent can scan for products with a 30%+ ROI, filter by price drop magnitude, and even set up hourly monitoring to alert the user when new flips clear the bar. This use case is particularly valuable for professional flippers, retail arbitrageurs, and algorithmic traders operating across multiple marketplaces.

Market Research and Competitive Intelligence

Product managers, analysts, and brand owners can use Kompy to gather comprehensive market intelligence from the Walmart ecosystem. By searching for products in a specific category, retrieving their detailed attributes, pricing, and seller offers, and analyzing customer reviews and ratings, users can understand market positioning, identify gaps, and assess competitive dynamics. The historical price data adds a temporal dimension, revealing seasonality, promotional patterns, and long-term pricing strategies of competitors. This intelligence informs product development, pricing strategy, inventory planning, and marketing campaigns with data-driven insights rather than anecdotal observations.

Automated Inventory and Supply Chain Management

Retailers and distributors can integrate Kompy into their supply chain systems to automate stock monitoring and replenishment workflows. The API can track stock status for thousands of SKUs in real time, triggering alerts or purchase orders when inventory levels drop below predefined thresholds. The per-seller granularity allows businesses to monitor specific suppliers or compare offers from multiple sellers to optimize procurement costs. Additionally, the historical stock data can be analyzed to predict demand patterns, identify out-of-stock risks, and improve inventory forecasting. This automation reduces manual effort, minimizes stockouts, and improves overall supply chain efficiency.

What is the difference between the REST API and the MCP server?

The REST API and MCP server provide access to the same underlying data and operations, but through different interfaces. The REST API is designed for traditional software development, where you make HTTP requests from any programming language using standard libraries or tools like curl. The MCP server, on the other hand, is designed for AI agents that speak the Model Context Protocol, such as Claude Code, OpenClaw, or Cursor. With MCP, agents discover the available tools (product lookup, search, history, reviews) automatically and can invoke them as native functions. Both interfaces use the same API key and credit system, so you can switch between them or use both simultaneously without additional configuration.

How does the credit-based pricing work?

Kompy operates on a credit-based pricing model where each API request consumes a certain number of credits based on the operation type and complexity. Credits are allocated monthly according to your subscription plan: the Hobby plan includes 14,000 credits per month, the Pro plan includes 45,000 credits, and the Business plan includes 180,000 credits. Unused credits do not roll over to the next month. You can monitor your credit usage in your account dashboard. If you exceed your monthly allocation, you can purchase additional credit packs or upgrade to a higher tier. Every new account starts with free credits to test the API before committing to a paid plan.

What data exactly does Kompy provide for a single product?

For a single product identified by its Walmart ID, Kompy returns a comprehensive JSON payload including the product name, brand, current price, currency, stock availability (boolean), average customer rating, total review count, seller name, and a timestamp of when the data was captured. Additionally, you can retrieve the product's full price and stock history per seller, customer reviews and ratings, and seller offer details. The response also includes metadata such as a unique request_id for tracing and the server latency in milliseconds. All data is structured, deterministic, and returned in under 50 milliseconds for most queries.

Is Kompy affiliated with or endorsed by Walmart?

No, Kompy is not affiliated with, endorsed by, or sponsored by Walmart Inc. It is an independent third-party service that provides structured access to publicly available Walmart marketplace data. The platform does not use any official Walmart API and instead aggregates data through its own proprietary methods, which are designed to be reliable, fast, and compliant with applicable laws and terms of service. Users are responsible for ensuring their use of Kompy complies with Walmart's terms of service and any applicable regulations.

Kompy offers three subscription tiers designed to scale from individual experimentation to large-scale production use. All plans include API access, MCP server access, and email support, with higher tiers adding priority support and custom integrations. The Hobby plan is priced at $49.99 per month and includes 14,000 credits, making it ideal for individuals getting started with the platform. The Pro plan, the most popular option, is $149.99 per month with 45,000 credits, suitable for professionals and small teams. The Business plan costs $499.99 per month and provides 180,000 credits along with priority support and custom integrations for large teams with custom needs. Every account begins with free credits to evaluate the service, and there are no hidden fees or forced upgrades. Users can compare all plans and features on the pricing page to select the tier that best matches their usage requirements.