ChatGPT's Next Update Could Wipe Out the Agent Layer
If OpenAI integrates MCP into ChatGPT, the agent wrapper ecosystem collapses
Several reports and developer discussions over the past few months have suggested that OpenAI is testing support fot the Model Context Protocol (MCP), a standard that would allow ChatGPT to connect directly to third-party tools through a structured interface. This includes a post on OpenAI’s developer forums titled “Preparing for MCP in Responses,” which outlines how users and services might integrate MCP endpoints into model outputs. While the post is hosted by OpenAI, the post is not an announcement from OpenAI of their intention to integrate MCP into ChatGPT. However the discussion includes a screenshot of a tweet from Sam Altman indicating as much:
So this is not a leak. OpenAI appears to be openly testing and documenting this feature. But if MCP is fully integrated into ChatGPT, it won’t just be a new developer feature. It will be an existential threat to startups whose entire premise is: “We built a thin agent shell around GPT-4 and connected it to some APIs.”
What is the Model Context Protocol?
The Model Context Protocol (MCP) is an open standard designed to expose third-party tools, services, or internal enterprise systems as structured context for AI models. It enables external applications to define how their data, actions, and state can be made machine-readable and accessible to a model like ChatGPT. It was developed by Anthropic as an open standard.
In practice, MCP would allows users or organizations to register an external tool, like GMail, Salesforce, or a custom internal dashboard, into ChatGPT by providing a connector definition. This would typically include:
A schema describing the tool’s interface and data types
An endpoint URL for the model to query or act upon
Permissions or access scopes for which data/action can be involved
The goal is to let the model use these tools as if they were native extensions of its own capabilities, without needing complex wrapper logic or manual data injection. Once configured, ChatGPT could ingest context from these sources, reason over it, and invoke actions programmatically in response to user queries or tasks.
MCP thus represents a generalization or formalization of earlier, more brittle plugin architectures. It’s not just a way for users to bolt on functionality. It’s a blueprint for how the model becomes the interface to everything.
The Squeeze is On
The core threat isn’t just that ChatGPT will do what these startups do. It’s that it will do it natively, faster, and without the startup in the loop. What today takes a team of engineers to orchestrate—routing GPT calls, integrating APIs, managing context windows—becomes a no-code connector within ChatGPT. The entire premise of the agent startup dissolves into a settings menu. The user never needs to leave the ChatGPT interface, never needs to trust a third-party wrapper, and never needs to pay for another middleman layer.
Here’s the structural collapse:
MCP would be OpenAI’s answer to the proliferation of agent wrappers. These are startups building superficial workflows around a model they do not control, with tools they do not own. Think “copilots,” “workflow bots,” “GPT-powered assistants for task X.” These companies would be caught in a classic platform squeeze.
If MCP is integrated directly into ChatGPT, OpenAI would:
Own the model (the substrate)
Own the UX (ChatGPT)
Now own the interface to external APIs
Your startup? Redundant.
This would not be a bug or a misstep. It would be a textbook play from the platform envelopment playbook. It’s Apple Sherlocking apps. It’s AWS launching one-click hosted clones. It’s Chrome absorbing your password manager.
Only this time, it’s worse, because the platform is the intelligence layer. It learns from you while it kills you.
The Agent Layer Was Never Real
The illusion many founders bought into over the last two years was that the model layer would stay stable and general-purpose, while a new “agent layer” would emerge to interpret user intent, route tasks, and manage context.
This was a seductive but false premise. Agent logic is not seperable from the model when the model itself is few-shot programmable, tool-aware, and increasingly memory-augmented. Agent wrappers are not defensible unless they:
Own proprietary domain-specific data
Solve deep vertical problems (e.g., pharma, defense)
Offer regulatory compliance layers (e.g., healthcare, banking)
Run on open-weight or in-house models
The rest? Replaceable with a native MCP connector.
From Orchestrators to Connectors
Today, an agent startup might:
Route GPT-4 output through a few internal APIs
Handle context injection from emails or CRMs
Call third-party tools to take actions
With MCP:
Those APIs could be directly available to ChatGPT
The context streamed into the session itself
The actions invoked natively via tool usage
MCP would turn the value of the agent startup into a 5-minute configuration form. Click “Add Connector,” enter your URL and schema, done.
Strategic Consolidation
This would be just the latest in OpenAI’s broader strategy to vertically consolidate the AI stack:
Build the model (GPT-4, GPT-5)
Serve the model (ChatGPT)
Integrate the context (MCP, memory, file uploads)
Deliver the output (voice, code, docs)
Every move shrinks the surface area for third-party innovation, unless it’s deeply embedded in data, infrastructure, or enterprise compliance.
It’s also worth distinguishing consumer-facing wrappers from enterprise-focused agents systems. The latter may retain some life due to procurement friction, internal compliance requirements, or highly bespoke workflows, but even those will feel increasing pressure as ChatGPT Enterprise matures.
What’s Left?
Agent startups would then face a stark choice:
Go deeper into verticals where OpenAI cannot or will not go
Pivot to tooling for model creators, not model consumers
Exit while you still have a story to tell
Otherwise, you “agent company” is just a connector config file that OpenAI hasn’t gotten around to autogenerating yet.
Final Thought
There is no moat in being a wrapper. There never was.
If MCP is integrated into ChatGPT, it will make this clear. The model is the platform. The agent layer is not a business model. It’s a temporary gap in OpenAI’s UX roadmap.
And that gap is closing fast.