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🦸🏻#14: What Is MCP, and Why Is Everyone – Suddenly!– Talking About It?

Community Article
Published March 17, 2025
Ksenia Se's avatar
Ksenia Se
Kseniase

everything you need to know about Model Context Protocol

“Even the most sophisticated models are constrained by their isolation from data – trapped behind information silos and legacy systems.” Anthropic, on why context integration matters

Large language models (LLMs) today are incredibly smart in a vacuum, but they struggle once they need information beyond what’s in their frozen training data. For AI agents to be truly useful, they must access the right context at the right time – whether that’s your files, knowledge bases, or tools – and even take actions like updating a document or sending an email based on that context. Historically, connecting an AI model to all these external sources has been a messy, ad-hoc affair. Developers had to write custom code or use specialized plugins for each data source or API. This made “wire together” integrations brittle and hard to scale.

To simplify that, Anthropic came up with Model Context Protocol (MCP) – an open standard designed to bridge AI assistants with the world of data and tools, to plug in many different sources of context. They announced it in November 2024. The reaction was sort of blah. But now MCP is trending, already passing Langchain and promising to overcome OpenAPI and CrewAI pretty soon. Major AI players and open-source communities are rallying around MCP, seeing it as a potential game-changer for building agentic AI systems. Why?

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In this article, we’ll dive deep into MCP – why it’s a hot topic right now, how MCP enables the shift toward more integrated, context-aware AI, its place in agentic workflows, and the under-the-radar details that developers, researchers, AI engineers, and tech executives should know. We’ll also explore some innovative applications of MCP that few have attempted. Overall, it’s a great starting guide, but also useful for those who have already experimented with MCP and want to learn more. Dive in!

For your convenience, we consolidate our AI explainers, practical guides, and deep dives in one place to help engineers, builders, and curious readers understand the fast-moving AI landscape. Read the complete article for free here: 🦸🏻#14:What Is MCP? Model Context Protocol in Agentic AI, Explained

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Community
loaspra

I like to view MCP as a higher lever of abstraction on tool usage. First came langchain with its tool functions, and now we have MCP servers that encapsulate a full feature and usability of a specific framework.
At first I thought that MCP were more related with the 'reasoning' part of the agent (well they maybe are bc the way tools are defined on the MCP server --markdown like instructions for each tool and the purpose of the MCP server-- they improve the overall performance of the agent).
But the most interesting fact about this is that Agent workflows will became more complex. Then we will improve even more the reasoning part (overall intelligence of the agents), maybe we will see more adversarial style of agents (just like MoE but on a higher level).

Interesting times ahead

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Kseniase
 Article author

Totally agree!
Mario1982

Thank you for this very interesting article!

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Kseniase
 Article author

You are very welcome
not-agent

You should definitely write about function calling vs. mcp!

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Kseniase
 Article author

great idea
ntzaz

This was super helpful. Got to know much about MCP in my first few articles. Looking forward to learn more!! Keep doing the good job in sharing the knowledge.

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Kseniase
 Article author

A2A overview coming soon!
Boeff

Very useful level of detail. It seems the major development is that the choice of tools has been moved from a hard-coded developer decision to a dynamic AI decision. Over the history of IDE development people kept discovering they had a computer available: "Oh wait, we have a computer available, we can do syntax highlighting" and then "Oh wait, we have a computer available we can do pre-compile code validation". Now we are in the stage of "Oh wait, we have an AI available". PS It seems the reference to Mahesh Murthy is an error.

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Kseniase
 Article author

It seems to work for me, check https://www.youtube.com/watch?v=kQmXtrmQ5Zg
dbur

Thank you for the insightful overview of MCP. I understand that MCP serves as a standardized integration layer for AI agents to perform actions involving external data or tools. Do you think entire agents themselves be served through MCP, or is MCP primarily designed for integrating individual tools and actions within an agent's workflow?

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Kseniase
 Article author

So far I think it's mostly for integrating tools. A2A is about agents and their communication. I will post a detailed overview of A2A here on Hugging face soon
harsid21

"Anthropic’s Mahesh Murthy delivered a workshop that went viral"
I am not sure the name is right. Isnt it Mahesh Murag? This is the workshop right? - https://www.youtube.com/watch?v=kQmXtrmQ5Zg

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Kseniase
 Article author

Thank you! Fixed (don't know how that happened, his name is correct in other places in the article)
Alexrware

"Such an informative blog! I liked how explicitly you wrote about how the Model Context Protocol (MCP) is operating in today’s AI ecosystem and how it is becoming more relevant. Your explanation of the pros and cons outlined the notion well from a developer perspective, especially those looking to the dynamic integration of tools into AI agents. Overall, it was a fair and pragmatic view of a quickly moving subject.

I also read a related article on ""https://mobisoftinfotech.com/resources/blog/ai-development/develop-use-mcp-server-ai-agents-maven-guide"", which dives deeper into the implementation side particularly around building and using MCP servers within AI agents using Maven. Together, both blogs give a complete perspective from understanding MCP’s purpose to actually putting it into practice."

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