Meet Bob... a senior developer at a fast-growing startup. His CEO just asked him to integrate their chatbot with Salesforce, Zendesk, and their internal database.
Bob's first thought? "Here we go again."
With their previous LLM provider, he spent three weeks building custom connectors. Each one was a tangled mess of API keys, authentication flows, and error handling. When the provider updated their API... everything broke.
Now they're switching to a different LLM because pricing changed. And Bob realizes with horror: none of his connectors will work. He needs to rewrite everything from scratch.
"There has to be a better way," Bob mutters, staring at his screen at 11 PM on a Friday.
Bob does the math... and it's depressing.
His company has 3 AI applications and needs to connect to 5 data sources. That's 3 times 5 equals 15 custom integrations.
But it gets worse. Each AI provider has a different format. When Bob adds a new data source, he doesn't write one connector... he writes three. When he swaps LLM providers? He rewrites all five connectors.
This is the M times N problem: connecting M applications to N data sources requires M times N custom integrations. The complexity grows exponentially... and Bob spends more time maintaining connectors than building features.
Then Bob discovers the Model Context Protocol... MCP.
MCP is like USB-C for AI. Just as USB-C lets you plug any device into any charger, MCP lets you connect any AI to any data source... with one standard protocol.
Before MCP: 15 custom integrations. New LLM? Rewrite all 5 connectors.
After MCP: Each AI implements MCP once. Each data source implements MCP once. Total: 8 implementations instead of 15.
When Bob adds Google Calendar, he writes one MCP server. All three AI apps can instantly use it.
MCP reduces M times N to M plus N. For 10 AI apps and 20 data sources, that's 30 implementations instead of 200.
Six months later... Bob's CEO asks for a new integration. Bob smiles. "Give me two hours."
He writes one MCP server. All three AI applications instantly have access. No custom logic for each app. No brittle connectors.
Better yet: Bob discovers an ecosystem of pre-built MCP servers. Google Calendar? Done. Figma? Claude Code now generates web apps from designs. Even Blender for 3D printing.
Write once, use everywhere.
When the CEO asks, "Can we switch to a cheaper LLM?", Bob says, "Sure. Everything will work."
This is the power of standards. USB-C created an ecosystem where innovation compounds. MCP does the same for AI.
Bob finally goes home at 5 PM. There was a better way.
Meet Bob... a senior developer at a fast-growing startup. His CEO just asked him to integrate their chatbot with Salesforce, Zendesk, and their internal database.
Bob's first thought? "Here we go again."
With their previous LLM provider, he spent three weeks building custom connectors. Each one was a tangled mess of API keys, authentication flows, and error handling. When the provider updated their API... everything broke.
Now they're switching to a different LLM because pricing changed. And Bob realizes with horror: none of his connectors will work. He needs to rewrite everything from scratch.
"There has to be a better way," Bob mutters, staring at his screen at 11 PM on a Friday.