MCP Servers: Give Your AI Superpowers
What if your AI could create GitHub issues, query your database, and post to Slack—all without you copy-pasting anything? That's what MCP servers do. Let's break it down.
So What's MCP Anyway?
MCP stands for Model Context Protocol. Fancy name, simple idea: it's a way for your AI to talk to other tools. GitHub, your database, Slack—you name it.
Think of it like giving your AI a set of keys to the tools you already use:
Your AI ↔ MCP Server ↔ External Tool (GitHub, Database, etc.)Instead of you going to GitHub, copying an error, pasting it into your AI chat, then copying the fix back—the AI just does it all in one conversation.
Why Would You Want This?
No More Tab Switching
Stay in your coding flow. Ask your AI "create an issue for this bug" and it just... does it. No browser tabs, no context switching.
Your Data Stays Local
MCP servers run on your machine. Your credentials, your rules. Nothing gets sent anywhere you don't want it to go.
Live Data, Not Stale Info
Your AI can query your actual database, check current GitHub issues, read today's Slack messages. Real data, real time.
The Most Useful MCP Servers
GitHub
Create issues, manage PRs, search code—all from your chat. This one's a game changer if you live in GitHub.
- "Create an issue for this bug I just found"
- "What are the open PRs on this repo?"
- "Review the changes in PR #42"
PostgreSQL / Supabase
Query your database without writing SQL. Great for quick data checks while debugging.
- "Show me the users table schema"
- "How many orders came in this week?"
- "Find users who haven't logged in for 30 days"
Slack
Post updates, read channels, catch up on discussions—without leaving your editor.
- "Post a deployment update to #engineering"
- "What did the team discuss in #bugs today?"
- "Send a message to @john about the API changes"
There's more: Linear, Notion, Sentry, Puppeteer, Brave Search... PairPrep supports 10+ MCP servers. Pick what you use.
How to Set This Up (It's Easier Than It Looks)
1Get Your API Keys Ready
You'll need tokens from the services you want to connect. Add them to your environment:
# Add these to your .zshrc, .bashrc, or .env
export GITHUB_TOKEN="ghp_your_token_here"
export DATABASE_URL="postgresql://user:pass@localhost:5432/mydb"
export SLACK_BOT_TOKEN="xoxb-your-token"2Add the MCP Server
Use the claude mcp add command:
# For GitHub
claude mcp add github --transport stdio -- \
npx @modelcontextprotocol/server-github
# For PostgreSQL
claude mcp add postgresql --transport stdio -- \
npx @modelcontextprotocol/server-postgresql3Test It Out
Ask your AI to do something with the new tool:
You: "List my recent GitHub repositories"
AI: I'll check your GitHub account...
[Uses github MCP server]
Found 5 repositories:
1. my-app (updated 2 hours ago)
2. api-service (updated yesterday)
...Stay Safe (Security Tips)
MCP servers are powerful—treat them with respect. Here's how to be smart about it:
Never Hardcode Secrets
Use environment variables. Keep them out of your code and version control.
Use Read-Only When You Can
If you only need to query data, use a read-only token. Less risk if something goes wrong.
Review Before Write Actions
Creating issues, posting messages—check what your AI is about to do before confirming.
Separate Tokens for MCP
Create dedicated API tokens for MCP. Easy to revoke if needed, won't affect your other tools.
What People Actually Use This For
Bug Hunting
"Check Sentry for the top 3 errors from today and create GitHub issues for each one."
Quick Data Checks
"How many users signed up this week? Anyone stuck on the onboarding step?"
Code Reviews
"Look at PR #123 and flag anything that might be a security issue."
Team Updates
"Summarize today's commits and post to #engineering on Slack."