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Andreas Horn on LinkedIn: ๐—›๐—ผ๐˜„ ๐—ฑ๐—ผ ๐˜„๐—ฒ ๐—ฐ๐—ผ๐—ป๐—ป๐—ฒ๐—ฐ๐˜ ๐— ๐—œ๐—Ÿ๐—Ÿ๐—œ๐—ข๐—ก๐—ฆ ๐—ผ๐—ณ ๐—”๐—œ ๐—ฎ๐—ด๐—ฒ๐—ป๐˜๐˜€โ€ฆ | 19 comments

  • Andreas Horn
  • 17 March 2025
  • 2 minute read
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This article was written by a Hotel Marketing Flipboard. Click here to read the original article

image

๐—›๐—ผ๐˜„ ๐—ฑ๐—ผ ๐˜„๐—ฒ ๐—ฐ๐—ผ๐—ป๐—ป๐—ฒ๐—ฐ๐˜ ๐— ๐—œ๐—Ÿ๐—Ÿ๐—œ๐—ข๐—ก๐—ฆ ๐—ผ๐—ณ ๐—”๐—œ ๐—ฎ๐—ด๐—ฒ๐—ป๐˜๐˜€ ๐˜€๐—ฒ๐—ฎ๐—บ๐—น๐—ฒ๐˜€๐˜€๐—น๐˜† ๐—ถ๐—ป ๐˜๐—ต๐—ฒ ๐—ณ๐˜‚๐˜๐˜‚๐—ฟ๐—ฒ?

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

Another potential solution? Model Context Protocol (MCP) โ€” 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.ย 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.ย 

๐—›๐—ผ๐˜„ ๐— ๐—–๐—ฃ ๐—ช๐—ผ๐—ฟ๐—ธ๐˜€? ๐— ๐—–๐—ฃ ๐—ณ๐—ผ๐—น๐—น๐—ผ๐˜„๐˜€ ๐—ฎ ๐—ฐ๐—น๐—ถ๐—ฒ๐—ป๐˜-๐˜€๐—ฒ๐—ฟ๐˜ƒ๐—ฒ๐—ฟ ๐—บ๐—ผ๐—ฑ๐—ฒ๐—น ๐˜„๐—ถ๐˜๐—ตย ๐˜๐—ต๐—ฟ๐—ฒ๐—ฒ ๐—ธ๐—ฒ๐˜† ๐—ฐ๐—ผ๐—บ๐—ฝ๐—ผ๐—ป๐—ฒ๐—ป๐˜๐˜€, ๐—ฎ๐—ฐ๐˜๐—ถ๐—ป๐—ด ๐—น๐—ถ๐—ธ๐—ฒ ๐—ฎย ๐˜‚๐—ป๐—ถ๐˜ƒ๐—ฒ๐—ฟ๐˜€๐—ฎ๐—น ๐—ฎ๐—ฑ๐—ฎ๐—ฝ๐˜๐—ฒ๐—ฟย ๐—ณ๐—ผ๐—ฟ ๐—”๐—œ ๐—ถ๐—ป๐˜๐—ฒ๐—ด๐—ฟ๐—ฎ๐˜๐—ถ๐—ผ๐—ป๐˜€ โ€” ๐˜€๐—ถ๐—บ๐—ถ๐—น๐—ฎ๐—ฟ ๐˜๐—ผ ๐—ต๐—ผ๐˜„ ๐—จ๐—ฆ๐—•-๐—– ๐˜€๐—ถ๐—บ๐—ฝ๐—น๐—ถ๐—ณ๐—ถ๐—ฒ๐˜€ ๐—ฐ๐—ผ๐—ป๐—ป๐—ฒ๐—ฐ๐˜๐—ถ๐—ป๐—ด ๐—บ๐˜‚๐—น๐˜๐—ถ๐—ฝ๐—น๐—ฒ ๐—ฑ๐—ฒ๐˜ƒ๐—ถ๐—ฐ๐—ฒ๐˜€:

1๏ธโƒฃ MCP Hosts โ€“ AI applications (like Claude) that provide the environment for AI interactions and facilitate access to external tools.ย 

2๏ธโƒฃ MCP Clients โ€“ 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.ย 

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3๏ธโƒฃ MCP Servers โ€“ These act as connectors, linking AI models with external systems like databases, file storage, or productivity tools (Google Drive, Slack, etc.).ย 

Itโ€™s early days, but this looks like an interesting option for the future of AI integration.ย 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:ย https://lnkd.in/djyS6Asa

Kudos to Norah Klintberg Sakal for this great graphic!

Please click here to access the full original article.

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