Andreas Horn on LinkedIn: 𝗛𝗼𝘄 𝗱𝗼 𝘄𝗲 𝗰𝗼𝗻𝗻𝗲𝗰𝘁 𝗠𝗜𝗟𝗟𝗜𝗢𝗡𝗦 𝗼𝗳 𝗔𝗜 𝗮𝗴𝗲𝗻𝘁𝘀… | 19 comments

𝗛𝗼𝘄 𝗱𝗼 𝘄𝗲 𝗰𝗼𝗻𝗻𝗲𝗰𝘁 𝗠𝗜𝗟𝗟𝗜𝗢𝗡𝗦 𝗼𝗳 𝗔𝗜 𝗮𝗴𝗲𝗻𝘁𝘀 𝘀𝗲𝗮𝗺𝗹𝗲𝘀𝘀𝗹𝘆 𝗶𝗻 𝘁𝗵𝗲 𝗳𝘂𝘁𝘂𝗿𝗲?

APIs? Probably too slow. Quite fragmented. And too much overhead. 

Another potential solution? Model Context Protocol (MCP) — a new open standard introduced by Anthropic that aims to make AI models more powerful by simplifying how they connect to external tools and data sources. Think of MCP « like a USB-C port but for AI agents: » It basically offers a uniform method for connecting AI systems to various tools and data sources.

Unlike traditional APIs, MCP provides both connectivity and built-in documentation/semantics, making integration smoother. And users can bring their own MCP servers to manage access to their own data and tools, offering a flexible approach to AI augmentation. 

𝗛𝗼𝘄 𝗠𝗖𝗣 𝗪𝗼𝗿𝗸𝘀? 𝗠𝗖𝗣 𝗳𝗼𝗹𝗹𝗼𝘄𝘀 𝗮 𝗰𝗹𝗶𝗲𝗻𝘁-𝘀𝗲𝗿𝘃𝗲𝗿 𝗺𝗼𝗱𝗲𝗹 𝘄𝗶𝘁𝗵 𝘁𝗵𝗿𝗲𝗲 𝗸𝗲𝘆 𝗰𝗼𝗺𝗽𝗼𝗻𝗲𝗻𝘁𝘀, 𝗮𝗰𝘁𝗶𝗻𝗴 𝗹𝗶𝗸𝗲 𝗮 𝘂𝗻𝗶𝘃𝗲𝗿𝘀𝗮𝗹 𝗮𝗱𝗮𝗽𝘁𝗲𝗿 𝗳𝗼𝗿 𝗔𝗜 𝗶𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻𝘀 — 𝘀𝗶𝗺𝗶𝗹𝗮𝗿 𝘁𝗼 𝗵𝗼𝘄 𝗨𝗦𝗕-𝗖 𝘀𝗶𝗺𝗽𝗹𝗶𝗳𝗶𝗲𝘀 𝗰𝗼𝗻𝗻𝗲𝗰𝘁𝗶𝗻𝗴 𝗺𝘂𝗹𝘁𝗶𝗽𝗹𝗲 𝗱𝗲𝘃𝗶𝗰𝗲𝘀:

1️⃣ MCP Hosts – AI applications (like Claude) that provide the environment for AI interactions and facilitate access to external tools. 

2️⃣ MCP Clients – Embedded within AI models, these format and send requests to MCP servers. If an AI model needs sales data from PostgreSQL, the MCP client structures the request accordingly. 

3️⃣ MCP Servers – These act as connectors, linking AI models with external systems like databases, file storage, or productivity tools (Google Drive, Slack, etc.). 

It’s early days, but this looks like an interesting option for the future of AI integration. And it’s a clearly structured approach that could enable more scalable, real-time AI integrations without the limitations of traditional API-based workflows.

Over to you! What is your take on MCP and its future?

Here is all the official MCP documentation and architecture: https://lnkd.in/djyS6Asa

Kudos to Norah Klintberg Sakal for this great graphic!