MCP is eating the world
10 months ago
- #AI
- #LLM
- #MCP
- Model Context Protocol (MCP) is simple, well-timed, and well-executed, making it likely to stay.
- Previous attempts like function/tool calling, ReAct/LangChain, ChatGPT plugins, and AutoGPT had limitations such as manual wiring, flakiness, and configuration complexity.
- MCP's success is attributed to four main factors: improved model robustness, a vendor-neutral protocol, good tooling, and strong ecosystem momentum.
- Newer LLMs are reliable enough to handle tool use without extensive error handling, reducing integration overhead.
- MCP provides a shared protocol, allowing tools to be defined once and used across any MCP-compatible LLM agent.
- MCP tooling is straightforward and high-quality, with SDKs available in multiple languages, lowering the barrier to entry.
- Momentum is strong with adoption by major model providers like OpenAI and Google Deepmind, and a growing ecosystem of registries, services, and tutorials.
- Stainless offers a free tool to generate MCP servers for REST APIs in minutes.