Cloudflare has revealed the inner workings of its proprietary AI engineering stack, built entirely on its own platform. In the last month, 93% of the company's R&D organization has leveraged AI coding tools powered by this internal infrastructure. This initiative, launched eleven months ago, aimed to deeply integrate AI into the engineering workflow, necessitating the creation of MCP servers, an access layer, and essential AI tooling.
A dedicated tiger team, dubbed iMARS (Internal MCP Agent/Server Rollout Squad), spearheaded the project, with the Dev Productivity team ultimately taking ownership. The numbers underscore the impact: 3,683 internal users actively engaged with AI coding tools, generating 47.95 million AI requests. Over 295 teams are utilizing these agentic AI tools, with AI Gateway processing 20.18 million requests and routing 241.37 billion tokens monthly. Workers AI alone processed 51.83 billion tokens.
The adoption of these tools has directly fueled developer velocity, evidenced by a dramatic increase in merge requests. The 4-week rolling average climbed from approximately 5,600 per week to over 8,700, peaking at 10,952 in late March, nearly doubling the Q4 baseline.
The architecture spans three core layers: platform, knowledge, and enforcement. The platform layer handles authentication, routing, and inference, leveraging Cloudflare Access for Zero Trust security, AI Gateway for centralized LLM control, and Workers AI for on-platform inference with open-weight models. The MCP Server Portal, built with Workers and Access, provides a single OAuth endpoint for multiple tools.
Platform Layer: Security and Developer Experience
Cloudflare Access ensures secure authentication and Zero Trust policy enforcement for over 3,600 internal users. All LLM requests are routed through AI Gateway, enabling centralized management of provider keys, cost tracking, and data retention policies. AI Gateway handles approximately 688,000 requests and 10.57 billion tokens daily, routing to four providers.
