Through the Model Context Protocol (MCP), AIs like Claude and ChatGPT are evolving into smarter personal assistants by connecting with external data.
Imagine this: One morning, you tell your smartphone AI assistant, “Summarize only the important emails I received yesterday and add them to today’s schedule.” Previously, this was impossible because the AI didn’t know the contents of your email. But now, such scenes are becoming reality. It is a magical change, as if the AI assistants have acquired a ‘common language.’ Today, I will easily explain ‘Model Context Protocol (MCP),’ the core of this innovation.
Why is this important?
Until now, artificial intelligences (AI) like Claude or ChatGPT, which we use, were very smart but like scholars sitting only in a library, disconnected from world news. Their knowledge was limited to the data they were trained on, and they couldn’t talk to our emails, company databases, or the work tools we use every day.
MCP is a technology that allows AI to walk out of this ‘library’ and work hand-in-hand with the work tools we actually use. Thanks to What is the Model Context Protocol?, AI is now evolving beyond a simple ‘chatbot’ into a ‘true agent’ that actually reads, organizes, and performs tasks with our data.
Easy to understand: The ‘Universal Power Outlet’ Analogy
To use a very easy analogy, MCP is like a ‘Universal Power Outlet.’
Previously, there were separate outlets for ChatGPT and Claude, but MCP is a standardized specification that allows you to plug in any electronic product (AI application) and use electricity immediately. Source: What is the Model Context Protocol?
Just as filters change the color tone of photos when we use a photo app on our smartphones, MCP acts as a passage that allows AI to safely look inside our data and filter out and bring only the necessary information. For example, when connecting ChatGPT with an email service, using MCP allows the AI to securely access the data source of your mailbox and read the contents. Source: How to connect ChatGPT to email
Current Status and Challenges
Currently, MCP is in its early stages but is being actively applied in the field. The AI services we commonly encounter are already tending to strengthen these linkage functions with external tools. Source: What is the Model Context Protocol?
However, the technology is not yet fully mature. As it uses new connection methods, ‘unexpected problems’ sometimes occur. In particular, when performing complex tasks using MCP connectors, errors sometimes occur where AI tools like Claude stop, saying, “The previous response is still running” because the previous task has not finished. Source: How to fix Claude response errors You can understand this phenomenon as a kind of ‘growing pain’ that technology goes through to move towards a more stable environment.
What will happen in the future?
Soon, we won’t have to worry individually about “where a tool is located” or “how to connect to it.” This is because AIs that understand local files on my computer, company cloud data, and personal mailboxes in a single ‘common language’ will emerge.
In the future, we will care more about ‘how safely and organically an AI connects and handles my data’ rather than how smart it is. MCP will be an important key to opening such an era, the era of ‘Connected AI.’
MindTickleBytes AI Reporter’s View
MCP goes beyond simply setting technical standards; it is a massive turning point that shifts data sovereignty from AI models to the ‘user.’ Ultimately, the real battleground will be how well the data the user possesses is connected and utilized, rather than performance competition between models.
References
- Technology to increase AI speed
- Technology to connect AI with external data, tools, and workflows
- Technology to train new AI models
- Upgrading computer graphics cards
- Connecting ChatGPT with email services
- Disconnecting from the internet
- Internet line disconnection
- Rapid battery drain
- Messages such as 'The previous response is still running'