Hi folks — I’m Vahid Madadi Mahani.I’m very excited about MCP, and I focus on using AI for SEO and digital marketing. I’m exploring Model Context Protocol (MCP) as a way for an AI assistant (e.g., Claude or your model of choice) to interact with n8n workflows and nodes—not just execute tasks, but also validate designs and control the build process. The idea: - Standardize access: AI reads tool docs via MCP, understands inputs/outputs, and selects the right n8n capability. - Design review: Assistant proposes a workflow plan (triggers, nodes, data paths); MCP exposes a validation tool to check schema, auth scopes, and idempotency. - Controlled execution: n8n runs the approved plan with retries, rate limits, and audit logs; AI only sees what MCP allows. Early blueprint I’m considering: 1. Minimal MCP toolbox: search.entities, db.query, cms.publish, queue.enqueue. 2. Guardrails: allowlisted resources, scoped tokens, size limits, content/PII lint. 3. Human-in-the-loop: approvals whenever publishing or touching prod data. 4. Run health: correlate MCP tool calls with n8n execution IDs for end-to-end traceability. For those who’ve tried similar AI-orchestrated builds: - What’s the smallest safe tool surface you’d start with? - Any tips for keeping prompts stable while tools evolve? Appreciate any feedback or gotchas you’ve encountered!

From Sketch to Production ## Overview This workflow represents a fully integrated AI development pipeline that handles everything from initial concepts to deployed applications using orchestrated AI tools and MCPs (Model Context Protocol servers). ## The Stack ### **Core AI Tools** - **Claude Desktop** - Ideation, design planning, and implementation specification - **Claude Code CLI** - Autonomous development with design review integration - **Warp AI** - Terminal automation, quick coding, and macOS integration ### **Design Pipeline** - **Sketch/Wireframe** → **Claude Desktop** → **Figma Make** → **Production Design** - **Figma MCP** - Design inspection and code generation guidance ### **Development MCPs** - **Context7** - Real-time library documentation and current best practices - **Playwright** - Live UI testing, screenshots, and interaction validation - **Design Review Agent** - Professional-grade UI/UX evaluation ### **Data Integration** - **FileMaker MCP** - Campaign and client data - **PostgreSQL/Supabase MCPs** - Project-specific database selection - **Vector Supabase MCP** - Shared project memory across all AI tools ## The Workflow ### **1. Ideation to Design** ``` Rough Sketch → Claude Desktop Refinement → Figma Make → Clean Design ``` Claude Desktop bridges concepts and execution, translating ideas into actionable design specifications. ### **2. Design to Code** ``` Figma Design → Claude Desktop Prompt Generation → Claude Code CLI Implementation ``` Highly effective prompt translation eliminates design-code disconnect. ### **3. Development Execution** - **Context7** ensures current library usage - **Database MCPs** provide real data integration - **Playwright** validates UI with live testing - **Vector memory** maintains context across tools ### **4. Quality Assurance** - **Design Review Agent** provides systematic UI/UX validation - **Style guide compliance** ensures consistency - **Multi-viewport testing** guarantees responsiveness