Yottaa Launches MCP Server for E-Commerce Performance Intelligence

Yottaa, providers of a cloud platform for e-commerce, has launched a Model Context Protocol (MCP) server to offer artificial intelligence-native access to web performance data for developers, engineers, and digital leaders.

Designed to bring real-time, structured performance data into developer workflows, the new MCP server enables AI agents and IDEs to query live production data and identify and act on site performance issues, from diagnosing third-party script impact to monitoring Core Web Vitals and JavaScript errors.

"MCP is more than just a new API; it's a fundamental shift in how developers can access and act on performance intelligence," said Gaetan Marmasse, chief technology officer of Yottaa, in a statement. "For the first time, web performance data is accessible directly from within code editors and AI assistants without jumping through dashboards or manual analysis. It's fast, AI-ready, and built with real-world e-commerce problems in mind."

Yottaa's MCP server supports natural language queries from compatible AI clients like Claude, Cursor, and VS Code Copilot. With minimal configuration, developers can ask questions like the following:

• "Which third-party apps are slowing down checkout?"
• "Are there anomalies in cart load time today?"
• "What JavaScript errors are impacting the product detail page?"

Each query returns structured responses in JSON format, optimized for reasoning by AI models or automated workflows.

"As more e-commerce brands adopt AI-powered tools, there's growing pressure to move beyond static dashboards," said Darin Archer, chief product officer of Yottaa, in a statement. "With our MCP server, we're giving developers a direct line to their site's performance health, eliminating guesswork and enabling real-time optimization at the speed of code."

Yottaa's MCP server provides iinstant insights and verified diagnostics across the following three key areas:

• Third-Party Impact Analysis - Automatically ranks all of a website's third-party vendors by precise millisecond contribution to page load times, empowering teams to hold vendors accountable and prioritize optimization.
• Anomaly Detection & Diagnostics - Uses machine learning to detect performance regressions, JavaScript errors, and behavioral anomalies, including trend context, root cause, and severity.
• Conversion Intelligence - For customers with Yottaa's conversion tracking, the MCP server connects performance metrics like Largest Contentful Paint (LCP) and Interaction to Next Paint (INP) directly to conversion rates and revenue, enabling ROI-based performance decisions.

Related Articles

Yottaa Launches Interactive Web Performance Index

Yottaa's updated Web Performance Index provides near-real-time e-commerce benchmarking.

Yottaa Launches Web Performance Services

Yottaa's Web Performance Services help companies fuel e-commerce speed and security.