Security Best Practices in AI and Model Context Protocol

As AI assistants and agent frameworks become more powerful, attackers are increasingly looking for ways to abuse them. The Model Context Protocol (MCP) makes it easy to connect tools and data sources to AI models—but that also means you must think like a security engineer when you expose those tools.

1. Treat Your AI Agent Like a Web App

Every tool you plug into your AI agent is similar to exposing an API endpoint on the internet. Before adding a new MCP tool, ask yourself:

• What data can this tool read or modify?
• What is the worst thing that could happen if it is abused?
• Does it need authentication, rate limiting, or audit logs?

If you would not expose an action directly to the public internet, you probably should not give it directly to an AI agent without strong guardrails.

2. Use Least Privilege for Tools

Do not give your AI agent full admin power over your infrastructure. Instead:

• Create read-only database roles for most tasks.
• Restrict filesystem access to a safe working directory.
• Limit external HTTP calls to a small set of trusted domains.

The goal is simple: if the model is tricked into doing something unexpected, the blast radius should be small.

3. Log Everything the Agent Does

Good logging turns AI behaviour from a black box into something you can monitor and improve. For each tool call, log:

• Which user triggered it.
• What tool was used and with which arguments.
• Whether it succeeded or failed.

These logs are extremely useful for both security investigations and improving the quality of your agent.

4. Keep Your Stack Patched

AI security is not only about the model. It is also about the framework, database, hosting platform, and any third‑party SDKs you use. Keep an eye on security advisories (like the Next.js CVEs) and patch quickly—your AI assistant is only as secure as the stack around it.

In this portfolio project, I practice these habits by securing my Next.js app, Neon database, and MCP tools the same way I would secure a production system—but at a student level, where I am still learning and improving.