Donating the Model Context Protocol and establishing the Agentic AI Foundation

Original Article ↗ Hacker News Discussion ↗

What MCP Is For (According to Commenters)

  • Seen by supporters as an API/protocol tailored for LLMs: standardized tool discovery, higher‑level workflows, richer descriptions than typical REST/OpenAPI.
  • Main value: easy “plug-in” integration with general-purpose agents (chatbots, IDEs, desktops) so end users can bring services like Jira, Linear, internal APIs, or factory systems into an AI assistant without custom wiring each time.
  • Several concrete examples: using MCP to manage Jira/Linear, connect internal GraphQL APIs with user-scoped permissions, or drive specialized backends (e.g., argument graphs) with LLM semantics on top.

Donation to Linux Foundation & Agentic AI Foundation

  • Some view the donation as positive: vendor neutrality, IP risk reduction, and a prerequisite for broader corporate adoption (e.g., large clouds won’t invest if a competitor controls the spec).
  • Others see it as a “hot potato” handoff or early “foundation-ification” of a still-turbulent, immature protocol, driven partly by foundation revenue models (events, certs).
  • Debate over whether this is the “mark of death” or normal standardization once multiple vendors are involved.

MCP vs APIs, OpenAPI, Skills, and Code-Based Tool Calling

  • Critics argue MCP is just JSON-RPC plus a manifest; OpenAPI or plain REST with good specs (Swagger, text docs) plus modern code-generating agents should suffice.
  • Pro‑MCP replies: most existing APIs are poorly documented for AI; MCP’s conventions and manifest explicitly signal “AI-ready”, self-describing tools.
  • Anthropic’s newer “skills” and code-first tool calling are noted as both a complement and a perceived retreat from MCP, though some point out MCP still handles dynamic tool discovery these approaches lack.
  • Alternatives mentioned: dynamic code generation in sandboxes, CLIs, simpler protocols like utcp.io.

Adoption, Maturity, and “Fad vs Future”

  • Split views:
    • “Fad/dead-end”: overkill abstraction, more MCP servers than real users, complexity without clear payoff.
    • “Here to stay”: rapid early adoption, especially among enterprises integrating many tools; fills the “chatbot app store” niche.
  • Concerns about reliability of multi-agent systems, protocol churn, and premature certifications.

Security, Governance, and Foundations

  • MCP praised for letting agents act via servers without exposing raw tokens/credentials, important for production and high-security environments.
  • Discussion of the Linux Foundation as both neutral IP holder/antitrust shield and, to some, a corporate dumping ground or form of “open-source regulatory capture.”