MCP Won't Solve Enterprise AI Integration (We're Missing a Layer)
Slack. Google. Microsoft. Salesforce. Reddit!?
I thought: finally — a standard way for AI to integrate with enterprise tools.
So I started building an enterprise MCP gateway.
Simple use case:
30,000 employees running Copilot or Claude.
All connecting to MCP tools.
Step 1: build a gateway.
Step 2: connect directory.
Step 3: assign MCP tools to users.
So far so good.
Then reality started stacking up.
Problem #1
You can’t let 30,000 employees authenticate directly to every MCP endpoint. So the gateway uses admin credentials.
Congrats.
Now your AI system technically has access to every Teams message in the company.
Problem #2
LLMs reason in natural language.
MCP tools expose REST wrappers.
Nancy asks:
“Summarize the marketing channel from yesterday.”
The tool expects:
get_messages(channel_id=847239)
So now you’re dynamically mapping IDs to names and rebuilding tool schemas per user.
Problem #3
OAuth tokens expire.
Now your gateway is refreshing tokens, retrying calls, translating requests, rebuilding responses, and basically turning into a giant middleware monster.
At this point I realized something:
MCP isn’t the problem, Nancy is not the problem either.
MCP It’s actually great.
But the industry is trying to use it to solve the wrong layer of the problem.
Trying to wire enterprise AI together through direct MCP tool connections is not architecture.
It’s integration chaos.
What we’re missing isn’t more connectors.
What we’re missing is ... well thats what I"m working on now, it involves abstract agent routing - like Layer 3.5 for AI.
Until then - I really care about Nancy and all the poor bastards working in large companies that will figure this out too but can't walk away because they need that two week pay.
Sense of humor but I"m making a point MCP = Missing Core Parts trying to use it on a enterprise level for AI Integration in a walled garden its just not going to work.