A Deep Dive into MCP and the Future of AI Tooling (a16z.com)

Model Context Protocol (MCP) is an open, agent-centric protocol (launched Nov 2024) that standardizes how LLMs call external tools, fetch data, and orchestrate multi-step workflows—think LSP for autonomous agents rather than editor features. Early adopters (Cursor, Claude Desktop) show how MCP clients can become “everything apps”: a code editor can invoke Slack, email (Resend), image generation (Replicate) or Blender/Unity servers to produce 3D assets from natural language. The ecosystem already includes server marketplaces (Mintlify mcpt, Smithery, OpenTools), server generators (Mintlify, Stainless, Speakeasy), hosting (Cloudflare, Smithery) and connection tooling (Toolbase), enabling rapid creation and discovery of MCP servers for dev-centric and consumer workflows. Technically, MCP today is mostly local-first, using SSE- and command-based connections and a one-to-many agent→tool model, but it lacks standardized auth, permissions, discovery, and stateful workflow primitives. Current auth is ad hoc (often OAuth 2.1 session-wide grants), making multi-tenant and remote deployments fragile. Pending upgrades—remote-first transports (Streamable HTTP), a registry/discovery protocol, unified auth/permission models, gateway patterns for routing/observability, and first-class resumable executions—are critical to scale MCP from developer experiments to production-grade agent-native infrastructure. If solved, MCP could dramatically reduce bespoke integrations, let agents dynamically select tools, and unlock new classes of AI-driven apps.