Secure
Manages AI model context through an enterprise-grade Model Context Protocol server, offering advanced security, scalability, and compliance for production AI deployments.
About
The Secure MCP Server provides a robust, enterprise-grade implementation of the Model Context Protocol (MCP), specifically engineered for demanding production AI environments. It prioritizes advanced security features such as Multi-Factor Authentication, SAML 2.0 integration, end-to-end encryption with certificate pinning, and HashiCorp Vault integration for secrets management. Designed for high availability and horizontal scaling, it leverages Kubernetes and offers comprehensive monitoring and observability with Prometheus and Grafana, alongside detailed audit logging to ensure compliance and reliable operation of AI systems.
Key Features
- Full Model Context Protocol (MCP) v0.5.0 implementation with WebSocket & HTTP support
- Advanced Security: Multi-Factor Authentication (JWT + TOTP/SMS), SAML 2.0 SSO, End-to-End Encryption (TLS 1.3), HashiCorp Vault Integration, RBAC
- Comprehensive Observability: Prometheus, Grafana, distributed tracing, and detailed audit logging for compliance
- 0 GitHub stars
- Efficient Context & Tool Management: Dynamic tool registration, validation, execution, and efficient context handling with caching
- Enterprise Scalability: Kubernetes-native Horizontal Scaling and Multi-region High Availability with automatic failover
Use Cases
- Building AI applications that need robust tool orchestration and dynamic context handling with high performance
- Deploying production AI agents and applications that require secure, scalable, and compliant context management
- Integrating AI models into enterprise systems with strict security requirements (e.g., SOC 2, ISO 27001)
