WeWeb MCP

WeWeb MCP is a connection layer that lets you build inside WeWeb with the AI agent you already use. You point Claude Code, Cursor, Codex, Antigravity, ChatGPT, or any MCP-compatible agent at WeWeb, and the agent builds the pages, workflows, data models, tables, authentication, and integrations that make up a real WeWeb project. Instead of producing code you cannot inspect, every change the agent makes lands in the WeWeb visual editor, where you can review it, keep prompting the agent, or edit it yourself. WeWeb MCP is aimed at builders and teams who want the speed of agentic development without giving up visual control over what actually ships. AI-assisted development has made it fast to generate application logic, but the output often arrives as a black box: it is hard to see exactly what changed, why it changed, or how to adjust it without another round of prompting. No-code tools solve the visibility problem, but traditionally require a person to click through every screen, workflow, and data relationship by hand. WeWeb MCP is positioned between those two worlds. It keeps the speed of an agent that can read a brief, plan structure, and wire data together, while keeping the result fully visible and editable in a visual environment. The stated goal is AI speed with visual control, so teams are not forced to choose between moving quickly and knowing what is inside their app. Connecting an agent to WeWeb follows three documented steps. First, you add the server configuration to your MCP client settings, using the WeWeb MCP endpoint through the mcp-remote command. Second, you sign in to WeWeb and authorize access so the agent can call tools on your project. Third, you pick your project and build: you can ask the agent to list your workspaces and projects, switch to the right one, and then describe what you want, for example building a dashboard page. The agent you bring can be Claude Code, which plans and builds in WeWeb using Claude's reasoning; Codex, which turns GPT-powered build plans into WeWeb apps; Antigravity, which builds with Gemini and Google models inside WeWeb; Cursor, which uses Cursor's agent and your model of choice; ChatGPT; or any other MCP-compatible agent. It runs on your account, your model, and your tokens. The product also starts from your brand's design DNA rather than a default AI look. You can import design rules and design context from Figma, Google Stitch, Claude Design, or design.md into WeWeb, so the agent has visual rules before it builds. From there you can create a component system using shadcn, React references, or custom coded components to build reusable blocks with no-code properties. A second major capability is turning PRDs into WeWeb apps. The agent reads a brief and creates the pages, forms, states, and flows users need, moving from user journeys to screens. It also maps data to backend structure, covering the database, fields, relationships, authentication, storage, and backend workflows behind the app. Finally, it turns business rules into integrations: Slack alerts, email triggers, CRM updates, API calls, and approval flows become part of how the app works. Importantly, the first version is not the final word, because everything stays editable after generation. WeWeb MCP is also designed to work across your wider MCP stack. You can pair WeWeb with a backend MCP such as Xano, Supabase, or Airtable MCP, or any APIs, to build the WeWeb frontend in context or bring data into the WeWeb backend. Product context can be turned into screens using docs, transcripts, websites, Figma files, or media assets to create onboarding, dashboards, and forms. A refactoring capability helps you move fast without creating maintenance debt: the agent can find unused variables, outdated workflows, test components, and leftover build artifacts, and it can standardize naming across pages, components, workflows, API requests, tables, and fields. Control features let you decide how much of the app the AI can touch, working across the full app or staying focused on one page, one workflow, or one database, and letting you control what happens next by reviewing output inside WeWeb before continuing. How the product works overall rests on the combination of an agent, a standard protocol, and a visual editor. The agent connects through MCP, the protocol used to give AI clients tool access, and calls tools on your WeWeb project once you authorize access. Because changes are applied to the WeWeb project rather than handed back as opaque text, the visual editor becomes the place where you inspect, adjust, and shape the result. You can scope the agent's access to the exact page, workflow, data, or design-system task you want changed, which keeps AI edits bounded and reviewable. When the app is ready, deployment is also part of the workflow: you can deploy in one click and launch on your custom domain while WeWeb handles hosting and infrastructure, or export code and run it on your own infrastructure when you need full control. The benefits described are speed with control, and ownership of the result. Teams get AI speed without the mystery of what changed in the app, because every change stays visual and reviewable. Because the agent runs on your account, your model, and your tokens, and because WeWeb states that WeWeb MCP does not use WeWeb AI credits, the cost and model choice stay under your control. Users keep the ability to keep prompting the agent or to open the visual editor and edit things themselves, so the app is never locked behind a generation process. Refactoring support helps prevent maintenance debt, and deployment options mean the app can go live on a custom domain or be self-hosted. Together these points support the claim that no-code does not mean low-performance, as expressed by a customer quoted on the site. Concrete scenarios described for WeWeb MCP include turning a PRD or brief into a working app with pages, forms, states, and flows; mapping a described data model into database structure with fields, relationships, auth, storage, and backend workflows; and translating business rules into integrations such as Slack alerts, email triggers, CRM updates, API calls, and approval flows. Another scenario is establishing a design system first, importing brand rules from Figma, Google Stitch, Claude Design, or design.md and building reusable components from shadcn, React references, or custom coded components. Teams also use it alongside backend MCP servers like Xano, Supabase, or Airtable to build the frontend in context. Finally, it can be used before launch to refactor an app by removing unused variables, outdated workflows, test components, and leftover build artifacts, and by standardizing naming across pages, components, workflows, API requests, tables, and fields. WeWeb MCP is for teams and builders who want agentic development with visual control, including those already using Claude Code, Cursor, Codex, Antigravity, or ChatGPT. The site highlights that the platform is trusted by Fortune 500 companies, showing logos for PwC, La Poste, L'Oréal, JLL, Qonto, Decathlon, Carrefour, and Biwaki by BNP Paribas, and it features testimonials from a Digital Project Manager at PwC, the CEO of Shunpo, and the CEO of ALOE Digital Solutions. WeWeb also documents that MCP works with the Cursor agent and your model of choice, with Claude Code, Codex, Antigravity, and ChatGPT, and with other MCP servers such as Xano, Supabase, and Airtable. The site offers the option to start for free and to request a demo, alongside calls to try for free. In summary, WeWeb MCP connects any MCP-compatible AI agent to WeWeb so that briefs, designs, and app logic become a real, structured WeWeb project. It combines agent speed with a visual editor, run on your own tokens and without WeWeb credits, keeps every change reviewable and editable, works alongside your existing MCP stack and backend tools, supports refactoring to avoid maintenance debt, and lets you deploy in one click or export and self-host. The core promise is straightforward: your AI agent builds the app, and you stay in control.