MCP Security: Best Practices for Production Deployments

When you deploy an MCP server to production, you are potentially granting an AI model direct access to your files, databases, APIs, and internal systems. MCP security is not optional—it is the foundation that determines whether your deployment empowers your team or exposes your infrastructure.

The MCP Threat Model

Primary Threat Vectors:

Malicious or compromised AI models
Prompt injection attacks
Insufficient access controls
Input validation failures
Information disclosure
Credential exposure

Transport Security

Local (stdio)

Process isolation provides some security. No network exposure. Suitable for development.

Remote (HTTP)

TLS is mandatory. Use TLS 1.3 where possible. Never deploy without encryption.

Authentication Patterns

API Keys

Simple authentication for service-to-service communication. Generate long, random keys. Rotate regularly.

OAuth Integration

Use OAuth when users grant MCP servers permission to act on their behalf. Implement proper token refresh and scope validation.

Authorization

Apply principle of least privilege. Implement tool-level permissions and resource access controls.

Input Validation

Always validate tool parameters
Use schema validation with Zod or similar
Prevent command injection and path traversal
Never trust AI-generated inputs

Secrets Management

Never hardcode credentials
Use environment variables or secret stores
Implement proper rotation

Logging and Auditing

Log authentication events, authorization decisions, and tool invocations. Never log sensitive data like passwords or tokens.

Security Checklist

TLS enabled for remote connections
Authentication required
Authorization enforced
Input validation implemented
Secrets properly managed
Comprehensive logging

Next Steps

In [Part 5](/blog/production-mcp-patterns), we cover production patterns for scaling and enterprise integration.

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