How to build a local MCP registry your security team will actually approve

2026-06-03 · Source: Stacklok · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Cybersecurity & Data Privacy, Cloud Computing & IT Infrastructure · Depth: Advanced, short

Summary

The article discusses building a local Model Context Protocol (MCP) registry to govern AI agent connections to production systems. It highlights the risks of ungoverned MCP deployments, such as credential leaks and lack of auditability, emphasizing that without a registry, each connection is uncontrolled. The post outlines six critical decisions for platform teams before deploying a registry: defining the user base, deployment location (VPC/on-premises vs. hybrid), authentication and authorization, server trust (attestation, scanning), observability, and granular server access control. Stacklok's MCP platform is presented as a solution, deploying as a Kubernetes Operator, integrating with existing identity providers like Okta, Microsoft Entra ID, and Google Workspace, using per-request identity tokens, isolating servers in containers with JSON-defined permissions, and providing OpenTelemetry/Prometheus observability. The platform also enforces explicit admin approval for servers via Kubernetes CRDs in version-controlled repositories.

Key takeaway

For MLOps Engineers or AI Architects deploying AI agents that connect to internal systems, you must implement a governed Model Context Protocol (MCP) registry to mitigate significant audit and security risks. Prioritize integrating your registry with an identity provider and defining granular access controls for each MCP server. This ensures auditability, prevents credential leaks, and limits the blast radius of any compromised server, transforming MCP from a liability into a secure enterprise capability.

Key insights

Ungoverned MCP deployments pose significant audit and breach risks; a well-governed registry transforms MCP into an enterprise capability.

Principles

• MCP deployments require robust authentication and authorization.
• Server code must undergo source attestation and vulnerability scanning.
• Granular access control limits the blast radius of compromised servers.

Method

Deploy an MCP registry as a Kubernetes Operator, integrating with existing identity providers. Enforce per-request identity tokens and isolate servers in containers with JSON-defined permissions.

In practice

• Connect your registry to an identity provider (e.g., Okta).
• Map 20-60 MCP servers, documenting sources and access.
• Onboard 3-5 low-sensitivity servers initially.

Topics

• Model Context Protocol
• AI Agent Governance
• Kubernetes Operator
• Identity and Access Management
• Software Supply Chain Security
• Observability

Best for: AI Security Engineer, MLOps Engineer, AI Architect

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Editorial summary, takeaway, and curation by AIssential. Original article published by Stacklok.