When I first got my hands on the Model Context Protocol (MCP), I felt like I’d unlocked a superpower — finally, a way to connect AI directly to tools like Google, Notion, and Slack.
But that excitement quickly turned into some very expensive and very humbling lessons. The truth? MCP is powerful, but it’s also a minefield if you’re not careful.
Thanks for reading! Subscribe for free to receive new posts and support my work.
Here’s what I wish I had known before diving in — straight from my own trial (and error) log.
1. The “Vague Prompt” Token Explosion
Early on, I asked the AI:
Find the Notion page called “2025Q3 roadmap”
Without a URL, the AI decided to go full detective — crawling through my entire workspace, testing method after method.
Cost: 80,000 tokens in one go.
When I simply gave it the exact page link, the cost dropped to 7,000 tokens. That’s over 90% saved just by being precise.
Lesson: Give the AI exact context — URLs, IDs, filters — so it doesn’t go on an expensive scavenger hunt.
2. The Data Access “Whoops”
I once connected MCP with a token that had full access to my Notion and Slack.
One wrong move, and the AI could’ve pulled data from everywhere.
Lesson: Follow least privilege — grant only what’s needed. Never reuse dev tokens in production, and keep scopes as narrow as possible.
3. The Multi-App Integration Rabbit Hole
Integrating MCP with Slack, Notion, and Google Drive sounded simple… until I mixed up token formats and got stuck regenerating credentials. Over. And over.
Lesson: Write down your setup steps. Store them securely. Test with small queries before committing to big workflows.
4. The “Local MCP” Reality Check
Local MCP hosting felt great for security — my data stayed on my machine. But non-technical teammates hit a wall the moment npx entered the picture.
Lesson: If your team isn’t all tech-savvy, either create a bulletproof installation guide
Final Takeaway
MCP can make AI feel like it’s part of your business brain — pulling the right data, across platforms, at the right time. But it only works that magic if you:
- Give clear, precise prompts
- Lock down your data access
- Document your integrations
- Balance security with usability
Small mistakes can cost you hours… or thousands of tokens. But with the right setup, MCP transforms AI from a clever chatbot into a decision-making, automation-driving partner. Try MCP on frevana app at frevana.com
Thanks for reading! Subscribe for free to receive new posts and support my work.