Enterprise AI Governance—
Secure, Auditable, Production-Ready

MXCP is an enterprise-grade building framework built on top of Model Context Protocol (MCP), the emerging standard for AI agent communication. While MCP provides the foundational protocol for AI agents to interact with external systems, MXCP adds the security, governance, and compliance layers that enterprises need for production deployments. Think of MCP as the communication standard, and MXCP as the enterprise-ready implementation with built-in policy enforcement, auditing, and access controls.

MXCP provides comprehensive AI governance through real-time policy evaluation, context-aware access control, and complete audit trails. It enforces policies against rogue AI behaviors, maintains compliance in zero-trust environments, and provides policy-as-code management with version control. Every AI agent interaction is monitored, logged, and evaluated against your governance rules before execution, ensuring your AI systems remain compliant and predictable.

Basic MXCP setup typically takes 10-15 minutes for a standard configuration. You can install it via pip and start with basic configurations immediately. However, enterprise deployments with custom policies, compliance requirements, and integration with existing systems usually require a more thorough setup process. We recommend starting with our open-source version to evaluate the framework, then working with our team for production deployment planning.

MXCP supports any AI agent that implements the Model Context Protocol (MCP) standard. This includes major AI platforms like Claude, ChatGPT, Gemini, and Grok, as well as any custom AI systems built to communicate via MCP. The framework is completely model-agnostic and enforces governance policies regardless of which AI provider you're using, ensuring consistent security and compliance across your entire AI infrastructure.

MXCP can securely connect AI agents to various enterprise data sources including APIs, databases, cloud storage, and file systems. The framework provides context-aware access control, meaning permissions can be dynamically adjusted based on data sensitivity, user roles, and AI agent context. All data access is logged and audited, ensuring complete visibility into what your AI systems are accessing and when.

Security is built into MXCP's core architecture with enterprise OAuth, API key management, role-based access control, and real-time policy evaluation. The system operates on a zero-trust model where every AI agent action must be explicitly authorized. We provide comprehensive observability to track what AI agents access, context-aware permissions that adapt to data sensitivity, and policy enforcement that can block unauthorized actions before they occur.

We provide multiple support channels including comprehensive documentation at mxcp.dev, an active community on Discord, open-source code on GitHub, and direct email support. For production deployments, we offer implementation consulting, custom integration support, and ongoing technical guidance. Our team has extensive experience helping organizations navigate AI governance challenges and can provide specific recommendations for your use case.

Yes, we offer managed MXCP solutions for organizations that prefer a fully managed approach to AI governance. Our managed service handles deployment, maintenance, monitoring, and updates while you focus on your core business. This includes automated scaling and enterprise-grade infrastructure management. Contact us to discuss your specific requirements and learn more about our managed offerings.