What problem does it solve? Building an MCP server from scratch involves many decisions—deployment model, transport, auth flow, tool design, and client configuration—that are easy to get wrong, producing servers nobody can run or connect. This Skill turns an "I want an agent that can do X" request into a complete, audited build pack covering everything from requirements to a runnable server. ## Core Features & Use Cases - Structured 7-stage workflow: discovery interview → mcp-prd.md → mcp-architecture.md → mcp-plan.json → scaffolded server → agent-design.md + ide-cli-matrix.md → automated audit plus a fresh auditor subagent scoring the pack out of 50. - Real server generation: scaffold-server.mjs validates the plan (kebab-case name, deployment model, auth mode, tool schemas) and generates a working @modelcontextprotocol/sdk server with zod-typed handlers, README, per-client config snippets, and .env.example. - Connection matrix for 9+ clients: exact connect commands for Claude Code, Cursor, Codex CLI, Gemini CLI, OpenCode, Cline, Windsurf, VS Code, and Zed, covering both stdio and remote HTTP deployments. - Use Case: Ask your agent to "build an MCP server that posts approved drafts to Instagram and X" and receive a full pack: PRD, architecture with OAuth 2.0 flow, a runnable server with post_draft/get_analytics/list_drafts tools, agent system prompt, and connect commands. ## Quick Start Ask your AI agent to build an MCP server for the capability you need, and it will run the discovery interview before scaffolding and auditing the deliverable pack.