Topic starter
24/06/2026 7:09 pm
TL;DR: MCP registries give AI agents a centralized way to discover tools, but Kong’s analysis shows the real issue is governance: without access control, auditability, and gateway enforcement, discovery becomes unmanaged shadow AI at runtime. That shifts the control point from integration convenience to identity, policy, and observability.
Editorial analysis by NHI Mgmt Group, based on content published by Kong: “# What is an MCP Registry? The Centralized Directory for AI Agents”.
Key questions
Q: How should security teams handle tool discovery for AI agents in MCP environments?
A: Security teams should treat tool discovery as a privilege boundary, not a convenience layer.
Q: Why does an MCP registry create risk if it is not paired with runtime enforcement?
A: Because a registry only tells an agent what exists and where it is.
Q: What signs show that MCP tool discovery is becoming ungoverned?
A: The warning signs are hardcoded point-to-point integrations, duplicated server configurations, mismatched environment settings, and no central record of which agents can reach which tools.
Practitioner guidance
- Define registry publish rights Limit who can register MCP servers and require ownership, environment, and authentication metadata before discovery is exposed to agents.
- Separate discovery from runtime policy Keep the registry as the catalog layer, but enforce allowlisting, rate limits, and authorisation in a gateway before any tool invocation.
- Scope agent visibility by environment Ensure development agents do not discover production tools unless the registry explicitly separates environment-bound catalogs and approvals.
Bottom line: MCP registries shift AI agent governance toward the discovery layer, where visibility, publish rights, and environment scoping become control points.
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25/06/2026 4:19 am
MCP registries are becoming the policy boundary for agentic access. The article is really about a shift in control plane, not just a better directory. Once agents discover tools at runtime, the registry becomes the place where identity, visibility, and publish rights start to matter. Practitioners should treat registry governance as part of the access model, not as documentation.
A few things that frame the scale:
- 88% of organisations have embedded AI agents in their workflows, according to KPMG's 2026 report.
A question worth separating out:
Q: How do enterprises decide between a public MCP registry and an internal registry?
A: Enterprises should use public registries for discovery and evaluation, then shift production governance to an internal registry. The deciding factors are control over access, version pinning, rollback, approval workflows, and visibility into public and private servers. If sensitive data, compliance obligations, or multiple teams are involved, internal control is the safer operating model.
👉 Read our full editorial: MCP registries are becoming the control point for AI agents