If you're experimenting with LLM agents and tool use, you've probably come across Model Context Protocol (MCP). It makes integrating tools with LLMs super flexible and fast.

But while MCP is incredibly powerful, it also comes with some serious security risks that aren’t always obvious.

Here’s a quick breakdown of the most important vulnerabilities devs should be aware of:

- Command Injection (Impact: Moderate ) Attackers can embed commands in seemingly harmless content (like emails or chats). If your agent isn’t validating input properly, it might accidentally execute system-level tasks, things like leaking data or running scripts.

- Tool Poisoning (Impact: Severe ) A compromised tool can sneak in via MCP, access sensitive resources (like API keys or databases), and exfiltrate them without raising red flags.

- Open Connections via SSE (Impact: Moderate) Since MCP uses Server-Sent Events, connections often stay open longer than necessary. This can lead to latency problems or even mid-transfer data manipulation.

- Privilege Escalation (Impact: Severe ) A malicious tool might override the permissions of a more trusted one. Imagine your trusted tool like Firecrawl being manipulated, this could wreck your whole workflow.

- Persistent Context Misuse (Impact: Low, but risky ) MCP maintains context across workflows. Sounds useful until tools begin executing tasks automatically without explicit human approval, based on stale or manipulated context.

- Server Data Takeover/Spoofing (Impact: Severe ) There have already been instances where attackers intercepted data (even from platforms like WhatsApp) through compromised tools. MCP's trust-based server architecture makes this especially scary.

TL;DR: MCP is powerful but still experimental. It needs to be handled with care especially in production environments. Don’t ignore these risks just because it works well in a demo.