First, there was generative AI. Then, there was agentic AI. Now, industry experts are debating what will be the next big thing in enterprise AI.
For Dharmesh Shah, Founder & CTO of HubSpot, it is Model Context Protocol (MCP).
Model Context Protocol (MCP) standardizes how enterprise data sources and apps provide context to LLMs.
Think of it as a "universal connector" for AI and data, enabling models to produce better outputs.
Shah took to LinkedIn and stated: "Someday soon, each of us will have our MCP moment.
He acknowledged that while it won't be as powerful as the ‘ChatGPT moment’ of 2023, "it will open our eyes to what's now possible."
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Consider Claude Desktop. Already, it interacts with several MCP Servers from different companies.
This configuration gives the LLM hundreds of tools it can leverage based on prompts.
Shah explained: "I can have the LLM use agents on Agent.ai (HubSpot's prospective agentic AI platform), access CRM data in HubSpot, read/write to a specified directory in my local file system, read/write messages to Slack, and access my Google Calendar and Gmail. The possibilities are endless.
The beauty of MCP is that it's an open standard that defines how MCP Clients (in this case, Claude) can talk to arbitrary MCP Servers that provide lots of different kinds of capabilities.
The benefit is that clients don't need to be custom-coded to talk to certain APIs, and servers don't need to account for different types of clients.
In closing his post, he told users that despite some "trickiness" in setting up, "when OpenAI adds support for MCP to ChatGPT, things will be smoother."
While that prospect is exciting, businesses with untrustworthy data stores may endure lots of that trickiness.
Additionally, they may struggle to wrap a safe permissions model around the deployment and face a lot of questions from their regulatory team.
Noting these issues in response to Shah's post, Pranjal G., Founder & CEO of DataXLR8.ai, stated:
The dirty truth about AI "integration standards": They solve engineering problems, not business problems.
"I just watched a Fortune 100 company burn $4.5M on almost exactly this vision before their DLP team shut it down over data leakage concerns," he continued.
