Icecat

Our Evolving Technology Stack: Embracing Python and Go

At Icecat, we chose to evolve our technology stack to ensure it remains aligned with the highest standards of performance, scalability, and developer experience.

As part of this evolution, we are officially adopting Python as our primary programming language and Go (Golang) as our high-performance language.

Python as Our Main Language

Python has become one of the most widely adopted programming languages in the world — recognized for its versatility, large ecosystem, and accessibility.

Its strong presence in the job market makes it an ideal choice for Icecat’s future growth, enabling us to build and scale our products efficiently while attracting top technical talent.

Go for Performance-Critical Services

While Python brings flexibility and speed of development, certain components in our infrastructure demand high throughput, concurrency, and efficiency.

For these specific use cases, Go will serve as our go-to language. Go ensures that robust, high-performance services are capable of handling large-scale operations across our ecosystem.

The MCP Server: Built with Go

Our MCP (Model Context Protocol) Server, which is expected to play a major role in Agentic AI and interoperability standards, is implemented entirely in Go.

This choice reflects our commitment to building a fast, scalable, and production-grade foundation for the e-commerce industry. It is based on what we see as a cornerstone protocol.

Phasing out Legacy Languages

As part of this transition, we consider PHP and Perl now legacy languages within our stack.

We will continue to support our legacy systems, but all new developments will be in Python or Go. Over time, existing modules will be progressively migrated to align with our modernized architecture.

Building for the Next Decade

This language strategy reinforces our focus on efficiency, maintainability, and long-term scalability.

By standardizing on Python and Go, we are laying the groundwork for a cleaner, more unified, and future-ready codebase. The new tech stack strategy helps to support Icecat’s mission to deliver high-quality, real-time product data to channel partners worldwide.

Together, we build the future of product content.

Guillaume Stritmatter

Recent Posts

JPMorgan Blocks Outside AI Agents Over Security Concerns

JPMorgan Chase is restricting third-party AI agents from accessing customer bank accounts, raising new questions…

13 hours ago

Building Partner Galleries in Brand Cloud and Multilingual MCP: Icecat Release Notes 261

Release 261 completes the partner gallery story. Release 260 delivered partner-specific galleries to every delivery…

4 days ago

Retailers Divided Over AI Shopping Agents as Agentic Commerce Expands

Retailers are taking different approaches to AI shopping agents, with some welcoming automated purchases while…

4 days ago

The Night We Were Ready to Switch Icecat Off

A 9.2 severity PHP flaw went public on Wednesday; the first scanner reached us the…

4 days ago

Story-in-Story, a Smarter AI Assistant & Framework v2: Icecat Studio – Sprint 106 Release Notes

Sprint 106 touched several parts of the platform. The AI Assistant got a new engine…

4 days ago

EU Product Identifiers from 1 November 2026: What NS-PID, S-PID and M-PID Mean for Sellers

From 1 November 2026, the EU requires product identifiers on the customs declaration for online…

5 days ago