Introducing Agent Lee - a new interface to the Cloudflare stack (opens in new tab)
Agent Lee is Cloudflare’s new in-dashboard AI assistant, designed to replace complex navigation with natural-language interaction across the Cloudflare platform. It can inspect account data, troubleshoot issues, and—when explicitly approved—make changes or deploy resources. Built on Cloudflare’s own infrastructure, it combines sandboxed code execution, permission controls, and generative UI to provide an interactive way to manage real accounts. ## A Natural-Language Interface to Cloudflare - Agent Lee understands account resources such as Workers, zones, DNS settings, and error rates. - Users can ask it to: - Identify the top error messages for a Worker. - Diagnose access problems involving a `www` prefix. - Enable Cloudflare Access for a domain. - Create an R2 bucket and connect it to a Worker. - It can retrieve account-specific context, use the appropriate tools, and present results through charts and other visualizations. - The beta reportedly serves about 18,000 daily users and performs nearly 250,000 tool calls per day across services including DNS, Workers, SSL/TLS, R2, Registrar, Cache, Cloudflare Tunnel, and API Shield. ## Codemode and Sandboxed Execution - Instead of exposing raw MCP tool definitions to the model, Agent Lee uses Codemode. - The model writes TypeScript that calls a generated API, which is intended to improve accuracy and support multi-step operations in a single script. - Generated code runs through a Cloudflare MCP server and a Durable Object acting as a credentialed proxy. - The Durable Object: - Classifies operations as reads or writes by inspecting the method and request body. - Proxies read operations directly. - Blocks write operations until the user explicitly approves them. - Keeps API keys out of generated code and injects credentials server-side. ## MCP Permissions and User Approval - Agent Lee connects to Cloudflare’s MCP server through: - A search tool for querying API endpoints. - An execute tool for running code that performs API requests. - Any operation that changes the account must pass through an elicitation step. - Approval is an enforced permission boundary rather than merely a confirmation-oriented interface feature. - Agent Lee cannot bypass the approval gate before executing writes. ## Built on Cloudflare’s Public Stack - Agent Lee uses the same building blocks available to Cloudflare customers: - Agents SDK - Workers AI - Durable Objects - Cloudflare’s MCP infrastructure - Cloudflare developed and tested the system in production against real accounts. - The company positions this approach as a way to identify platform limitations and validate patterns that other developers can reuse. ## Generative UI - Agent Lee supplements text responses with dynamically generated interface components. - Questions about traffic can produce interactive line charts rather than plain numerical summaries. - An adaptive grid lets users reserve space for new UI blocks by dragging across the interface and describing what they want. - Supported components include: - Tables - Interactive charts - Architecture maps - Other dynamic visual blocks - The result is intended to turn conversation history into an evolving operational dashboard. ## Quality and Safety - Elicitations are used whenever Agent Lee needs to perform a non-read action, requiring explicit approval in the interface. - Cloudflare also evaluates the system’s: - Conversation success rate - Information accuracy - Because the product remains in beta, users may encounter limitations or edge cases as its reliability and performance continue to improve. Agent Lee’s central promise is to make Cloudflare operations conversational without removing control. Its most important design choice is the combination of broad account awareness with a structural approval gate for changes, while its generative UI makes the resulting information and workflows more actionable.