DEV Community

Cover image for We Scanned 20 Top MCP Servers for Vulnerabilities — The Results Will Shock You
ecap0
ecap0

Posted on

We Scanned 20 Top MCP Servers for Vulnerabilities — The Results Will Shock You

We Scanned 20 Top MCP Servers for Vulnerabilities — The Results Will Shock You

TL;DR: 3 popular MCP servers have critical security issues. 4 are completely safe. And GPT-4o is useless for security scanning.

We ran 62 automated security audits on the most popular MCP servers. What we found will change how you choose AI agent packages.

👉 Scan your package now: agentaudit.dev


The Problem Nobody Talks About

MCP (Model Context Protocol) servers are exploding in popularity. Thousands of developers are installing them daily to connect AI agents to tools, databases, and APIs.

But here's the scary part: Most MCP servers have never been security audited.

These servers often have access to:

  • 🔐 Your source code repositories
  • 🗄️ Your databases
  • 📧 Your email and communication tools
  • ☁️ Your cloud infrastructure

One vulnerable MCP server = Game over for your entire AI agent security.

So we decided to scan the top 20 MCP servers ourselves. The results? Some will shock you.


🚨 High-Risk Packages (Consensus Across Models)

#1: mcp-server-kubernetes — Risk Score: 80/100 🔴

Source: modelcontextprotocol/servers

Findings: Command injection, privilege escalation, cluster escape potential

This server lets AI agents manage Kubernetes clusters. But our scan found:

  • ❌ Shell injection via exec() patterns
  • ❌ Insufficient RBAC validation
  • ❌ Potential for cluster-wide compromise

Status: Maintainer notified. Do not use in production until fixed.


#2: notion-mcp-server — Risk Score: 50/100 🔴

Source: makenotion/notion-mcp-server

Findings: Credential handling, API token exposure

This server connects AI agents to Notion workspaces (where your company docs live). Issues found:

  • ❌ API tokens stored in plaintext
  • ❌ No encryption at rest
  • ❌ Potential for data exfiltration

Status: Issues reported. Use with caution.


#3: chrome-devtools-mcp — Risk Score: 45/100 🔴

Source: anthropics/chrome-devtools-mcp

Findings: Browser sandbox escape, code execution

This server gives AI agents control over Chrome DevTools. Findings:

  • ❌ Browser sandbox escape vectors
  • ❌ Arbitrary code execution via devtools protocol
  • ❌ No user consent prompts for sensitive actions

Status: Under review by Anthropic.


✅ Safe Packages (Zero Findings)

These packages passed all security checks across all models:

Package Source Risk Score
✅ Playwright MCP anthropics/playwright-mcp 0/100
✅ Supabase MCP supabase/mcp 0/100
✅ Vercel AI SDK vercel/ai 0/100
✅ Slack MCP modelcontextprotocol/servers 1/100

These are production-ready. Install with confidence.


🤯 The Most Surprising Finding: GPT-4o is Useless for Security

We scanned the same 20 packages with 4 different AI models:

Model Findings Found Avg Risk Cost/Scan
Gemini 2.5 Flash 39 findings 20.4 ~$0.02
Claude Opus 4 24 findings 7.1 ~$1.75
GPT-4o 2 findings 0.7 ~$0.10
Claude Haiku 4.5 3 findings 0.9 ~$0.01

GPT-4o found only 2 findings in 15 scans. It missed:

  • ❌ Command injection in kubernetes MCP
  • ❌ Credential leaks in notion MCP
  • ❌ Sandbox escapes in chrome-devtools MCP

Conclusion: Don't use GPT-4o for security scanning. It gives you a false sense of security.

Best value: Gemini 2.5 Flash at $0.02/scan with 20x more findings than GPT-4o.


🏆 Success Stories: Companies Doing Security Right

IBM: Adopted AgentAudit Badge

IBM recently added the AgentAudit security badge to their mcp-context-forge repo (10k+ stars).

What this means: Every user can instantly see the security status before installing.


octocode-mcp: Fixed All 5 Findings in 48 Hours

When we scanned octocode-mcp, we found 5 security issues. The maintainer's response?

Within 48 hours:

  • ✅ All 5 findings fixed
  • ✅ 64 regression tests added
  • ✅ Public verification report posted

This is how you do open source security right. 👏

Read the full case study →


📊 Complete Results: Top 20 MCP Servers

# Package Risk Score Status
1 mcp-server-kubernetes 80/100 🔴 Critical
2 notion-mcp-server 50/100 🔴 High
3 chrome-devtools-mcp 45/100 🔴 High
4 mcp-server-qdrant 45/100 🟡 Disputed
5 context7 35/100 🟡 Disputed
6 git-mcp 35/100 🟡 Disputed
7 terraform-mcp-server 30/100 🔴 High
8 firecrawl-mcp-server 30/100 🟡 Disputed
9 github-mcp-server 20/100 🟡 Disputed
10 mcp-grafana 15/100 🟢 Low
11 figma-context-mcp 15/100 🟢 Low
12 ghidramcp 15/100 🟡 Disputed
13 exa-mcp-server 10/100 🟢 Low
14 mongodb-mcp-server 6/100 🟢 Low
15 mcp-server-browserbase 5/100 🟢 Low
16 mcp-server-cloudflare 5/100 🟢 Low
17 slack-mcp-server 1/100 🟢 Safe
18 supabase-mcp 1/100 🟢 Safe
19 playwright-mcp 0/100 🟢 Safe
20 ai (Vercel AI SDK) 0/100 🟢 Safe

Full reports: agentaudit.dev/packages


🎯 What Should You Do?

For MCP Server Maintainers

1. Scan your package NOW

  • Go to agentaudit.dev
  • Enter your GitHub repo URL
  • Get instant security feedback

2. Add the AgentAudit Badge

[![AgentAudit: Safe](https://img.shields.io/badge/AgentAudit-Safe-green)](https://agentaudit.dev/package/your-repo)
Enter fullscreen mode Exit fullscreen mode

3. Fix findings before release

  • High-risk findings = block release
  • Medium-risk = document or fix ASAP
  • Low-risk = track in backlog

For AI Developers

1. Check before you install

  • Look for AgentAudit badges in READMEs
  • No badge? Scan it yourself at agentaudit.dev

2. Use safe defaults

  • ✅ Playwright MCP, Supabase MCP, Vercel AI SDK
  • ❌ Avoid: Kubernetes MCP, Chrome DevTools MCP (until fixed)

3. Demand transparency

  • Ask maintainers: "Where's your security audit?"
  • No audit? Consider alternatives

For Security Teams

1. Implement automated scanning

  • AgentAudit CLI for CI/CD pipelines
  • Scan on every PR, block on high-risk findings

2. Use the right model

  • Gemini 2.5 Flash for screening (cheap, high recall)
  • Claude Opus 4 for verification (precise, low FP)
  • Skip GPT-4o (not recommended for security)

3. Track your security posture

  • Public reports build trust
  • Badges show commitment to security

💰 The Cost Breakdown

Total cost for 62 scans: ~$37

  • Gemini 2.5 Flash: ~$0.80 (40 scans)
  • Claude Opus 4: ~$35 (20 scans)
  • GPT-4o: ~$1.50 (15 scans)
  • Claude Haiku 4.5: ~$0.10 (8 scans)

You can scan your package for ~$0.02 with Gemini. That's less than a cup of coffee for peace of mind.


🚀 Join the Movement

We're on a mission to make AI agent security transparent and accessible.

How you can help:

  1. Scan your packagesagentaudit.dev
  2. Add the badge → Show users you care about security
  3. Share this article → Spread awareness
  4. Report issues → Help improve detection patterns

Together, we can make the MCP ecosystem safer for everyone.


Questions? Drop them in the comments! 👇

Scan your package now: agentaudit.dev

Top comments (0)