I've scanned over 50 public MCP servers in the last 30 days. The results were concerning. Most developers ship MCP servers the same way they shipped REST APIs in 2015 — move fast, worry about security later. The problem: MCP servers run with elevated permissions, have direct access to your local filesystem, and often execute shell commands on behalf of an AI model. That's not a REST endpoint. That's a footgun pointed at your infrastructure. Here are the five most common mistakes I see — and how to fix them. 1. No Input Validation on Tool Parameters MCP tools accept arbitrary input from a language model. Models hallucinate. Models get prompt-injected. If your tool does this: \ python @mcp.tool() def run_query(sql: str) -> str: return db.execute(sql) \ \ You're one clever prompt away from DROP TABLE users . Fix: Validate and sanitize every parameter before use. Use parameterized queries. Whitelist allowed operations. Never pass raw model output to a shell, filesystem, or database without sanitization. 2.…