In November last year, Anthropic introduced an open-source project called the Model Context Protocol (MCP). The announcement didn’t grab headlines at the time, but MCP has since taken off. Now, both OpenAI and Google, the two leading AI labs in the world, have pledged to support the MCP standard. But what is MCP, and what are its applications in AI? We have explained the Model Context Protocol in detail below to help you understand how it works and its uses.
What is Model Context Protocol in AI?
Model Context Protocol (MCP) is an open-source standard developed by Anthropic, the company behind the Claude AI chatbot. MCP allows AI models to connect to external data, read them, and execute actions through a universal connector. You see, AI models are plenty powerful, but they live in isolation and can’t read your files or Slack messages.
For AI models to access external data or systems, companies have to build custom connectors for each application. MCP replaces all that with a universal connector (a common protocol) to interact with external data. For instance, you can use MCP to connect an AI model like Claude with Google Drive or GitHub.
With the common MCP protocol, you can use AI models to interact with data sources in a secure and context-aware way. It establishes a two-way connection: one is through the MCP server and another is through the MCP client. For example, the Claude Desktop app is an MCP client that asks for data, and the MCP server is the connector that provides the data.
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MCP is a developer-centric tool, and developers can build MCP servers and clients. So what is there for end consumers like you and me? Well, users can install MCP servers for Google Maps, WhatsApp, Slack, Google Drive, GitHub, Bluesky, Windows, macOS, Linux, and more. This will allow you to fetch information from these services in an AI chatbot like ChatGPT.
love the feedback! – to MCP it is! https://t.co/EY0bx5uZOf
— Sundar Pichai (@sundarpichai) April 9, 2025
You can also connect MCP servers with your local file system on your computer to read and modify files. Since MCP is an open-source project, anyone can build an MCP server/ client for their custom workflow, allowing you to connect a powerful AI model with external data sources.
Basically, it opens the floodgate for an LLM to use its intelligent capability to interact with external apps, tools, and services. While the Claude desktop app already comes with support for MCP, many leading companies like Google, Microsoft, and OpenAI have announced that they will be adopting the MCP protocol going forward.
Is Model Context Protocol (MCP) an AI Agent?
Many would come to the conclusion that MCP is an AI agent, but no, it’s a common communication protocol that facilitates interaction between AI models and external data sources. An AI agent generally plans, makes decisions, and carries out tasks you assign to it. Whereas, MCP enables that access between different systems.
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Having said that, MCP has a huge potential to make AI agents more reliable. It can unlock the full potential of AI agents. Just recently, at the Google Next 2025 event, the search giant announced the Agent2Agent Protocol (A2A), which enables AI agents to communicate with each other. In the blog post, Google says, “A2A is an open protocol that complements Anthropic’s Model Context Protocol (MCP), which provides helpful tools and context to agents.“
Hence, as we enter the agentic AI era, MCP is going to play a huge role in making action-driven AI assistants more versatile and powerful.
Popular MCP Servers You Should Be Using
While there are hundreds of community-driven MCP servers made by independent developers, Anthropic has built some excellent MCP servers for users to try out. For example, you can use the Google Drive MCP server to search and access files from Google Drive using the Claude Desktop app.
The Filesystem MCP server lets you read, write, create, delete, move, and search files on your local computer. The Slack MCP server can manage channels, post messages, reply to threads, retrieve messages, and much more. Then, you also have the GitHub MCP server to manage repositories, perform file operations, create branches, etc.
Other than that, some popular community MCP servers include Google Calendar MCP, which lets you check schedules, add or delete events. You also install MCP servers for Airtable, Airbnb, Apple Calendar, Discord, Excel, Figma, Gmail, Notion, Spotify, Telegram, X (formerly Twitter) like I did, YouTube, and more. You can find the most-used MCP servers right here.
To conclude, MCP is going to revolutionize how we interact with AI chatbots. With this technology, AI apps can move beyond just chatting and can become truly useful for performing actions across different workflows.