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🔐 MCP Security Checklist

A practical, community-maintained security checklist for teams building and deploying Model Context Protocol (MCP) servers and AI agent infrastructure.

License: MIT Maintained by Helixar Contributions Welcome GitHub Stars


Why This Exists

MCP is being adopted rapidly. Security guidance is lagging behind.

This checklist gives security engineers, platform teams, and technical leaders a clear, actionable baseline for securing MCP deployments — whether you're shipping an internal tool or a customer-facing AI agent.

It is not vendor-specific, complete, or a replacement for a full security review. It is a starting point.


📋 The Checklists

Checklist Audience Description
Authentication & Authorization All Identity, token scope, and access control
Input Validation & Prompt Injection Engineers Sanitizing inputs before tool execution
Tool & Resource Exposure Engineers / Architects Limiting blast radius of MCP tools
API Session Security Platform Teams Securing inbound sessions from agents
Monitoring & Observability SecOps What to log, alert on, and review
Network & Infrastructure Platform Teams Network-layer hardening
CISO Summary CISOs / Leadership Non-technical risk summary

✅ Quick-Start: Top 10 Controls

If you do nothing else, cover these:

  1. Never expose MCP over the public internet without mTLS or equivalent.
  2. Scope every tool to the minimum necessary permissions.
  3. Validate and sanitize all inputs before they reach tool execution.
  4. Log every tool invocation with the originating session context.
  5. Set rate limits on both the MCP server and any downstream APIs it calls.
  6. Treat agent sessions as untrusted by default — validate intent, not just auth tokens.
  7. Separate read and write tool categories; require explicit approval for write operations in sensitive contexts.
  8. Rotate credentials used by MCP servers on a defined schedule.
  9. Monitor for behavioral anomalies: unusual tool chains, high-frequency calls, off-hours access.
  10. Conduct a tool inventory review before every production deployment.

🗂️ Machine-Readable Version

A JSON and YAML version of the checklist is available for integration into CI/CD pipelines, compliance tooling, or custom dashboards:


🌐 GitHub Pages Site

Browse the checklist in a friendlier format at: helixar-ai.github.io/mcp-security-checklist


🤝 Contributing

This checklist improves through community input. If you've encountered a gap, misconfiguration, or attack pattern in real-world MCP deployments — we want to hear about it.

See CONTRIBUTING.md for how to get involved.


📌 Scope & Limitations

This checklist covers:

  • MCP server deployment and configuration security
  • Inbound session and API request security
  • Agent-to-tool interaction surface
  • Operational monitoring and detection

This checklist does not cover:

  • Model weights or training pipeline security
  • End-user data privacy compliance (GDPR, CCPA, etc.)
  • General cloud infrastructure hardening

🏷️ License

MIT. Use it freely. Attribution appreciated.


Maintained by the Helixar security research team. Helixar builds AI-native endpoint and API security for agentic infrastructure.

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MCP is being adopted rapidly. Security guidance is lagging behind. This checklist gives security engineers, platform teams, and technical leaders a clear, actionable baseline for securing MCP deployments , whether you're shipping an internal tool or a customer-facing AI agent.

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