Cadre

Capstone 13 — MCP Server with Registry and Governance

The Model Context Protocol stopped being the future and became the default tool-use spec in 2026. Anthropic, OpenAI, Google, and every major IDE ship MCP clients. Pinterest published its internal ecosystem of MCP servers. The AAIF Registry formalized capability metadata at `.well-known`. AWS ECS published the reference stateless deployment. Block's goose-agent put the same protocol inside a hosted assistant. The 2026 production shape is: StreamableHTTP transport, OAuth 2.1 scopes, OPA policy gating, and a registry that lets platform teams discover, validate, and enable servers. Build that end to end.

Capstone 25 hr Python (server, via FastMCP) or TypeScript (@modelcontextprotocol/sdk), Go (registry service)

Prerequisites: Phase 11 (LLM engineering), Phase 13 (tools and MCP), Phase 14 (agents), Phase 17 (infrastructure), Phase 18 (safety)

#Problem

MCP became the tool-use lingua franca. Claude Code, Cursor 3, Amp, OpenCode, Gemini CLI, and every managed agent now consume MCP servers. The production challenges are not authoring servers (FastMCP makes that easy) but deploying them at scale with enterprise requirements: per-tenant OAuth scopes, OPA policy on destructive tools, StreamableHTTP stateless scaling, a registry for discovery, audit logs per tool call. Pinterest's internal MCP ecosystem and the AAIF Registry spec set the 2026 bar.

You will build an MCP server exposing 10 internal tools (Postgres read-only, S3 listing, Jira, Linear, Datadog, etc.), a registry UI for platform discovery, and a human-approval gate for destructive tools. The load test demonstrates StreamableHTTP horizontal scaling. The audit trail satisfies an enterprise security review.

#Problem

Keep going. The rest of this lesson is one step away.