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!