MCP registries are becoming the control point for AI agents

At a glance

What this is: This is Kong’s explanation of MCP registries as the discovery layer for AI agents, with the key finding that registry design only becomes useful when it is tied to governance and runtime enforcement.

Why it matters: It matters because IAM, PAM, and NHI teams now have to govern which agents can discover, authenticate to, and invoke tools across environments, not just manage static machine credentials.

👉 Read Kong's guide to MCP registries for AI agent governance

Context

An MCP registry is a discovery catalog for AI agents, not a tool runtime. The governance problem starts when agent-to-tool connections are hardcoded point to point, because that creates configuration drift, duplicated integrations, and no reliable way to see which agents are accessing which tools.

For identity teams, the important question is not whether agents can find tools faster. It is whether discovery can be bound to access policy, environment separation, and audit trails so that autonomous consumers do not turn tool sprawl into unmanaged access sprawl.

Key questions

Q: How should security teams govern AI agents that discover tools at runtime?

A: Security teams should treat agent tool discovery as an access event, not a documentation lookup. Put approval, ownership, and environment controls around the registry, then enforce policy again at runtime through a gateway or equivalent control. Without both layers, discovery becomes an unmanaged path into production tools and data.

Q: Why do MCP registries create new IAM and NHI governance requirements?

A: Because they centralize the discovery of machine-consumable tools, they also centralize the point where policy can fail. If the registry exposes stale, excessive, or unowned tool entries, agents can reach services that were never meant to be broadly discoverable. That makes registry governance part of NHI lifecycle control.

Q: What breaks when AI agents can access tools without a central registry?

A: Teams lose the ability to see, standardize, and revoke tool access consistently. Each agent carries its own connection logic, which creates drift, duplicated work, and weak accountability. The result is scattered machine access that is hard to audit and harder to retire cleanly.

Q: What is the difference between an MCP registry and an MCP gateway?

A: A registry helps agents discover tools and connection metadata. A gateway decides whether the agent is allowed to use those tools and under what constraints. Enterprises need both, because discovery without enforcement leaves access uncontrolled, while enforcement without discovery forces rigid hardcoded integrations.

Technical breakdown

MCP registry discovery versus gateway enforcement

An MCP registry stores metadata about tools, servers, and authentication requirements so agents can discover what exists and how to connect. It does not sit in the data path. An MCP gateway is different: it enforces runtime policy, authentication, rate limits, and observability once the agent connects. The architectural mistake is treating discovery as governance. Discovery answers what is available, while enforcement answers whether the agent should be allowed to use it under current policy.

Practical implication: separate catalog governance from runtime enforcement, then ensure both share identity and policy context.

Why point-to-point agent integrations create governance debt

Without a registry, every agent carries its own connection definitions for each tool. That creates duplicated configuration, inconsistent endpoint data, and no single place to revoke access across all consumers. In practice, the identity problem is not just authentication. It is lifecycle control over machine consumers that can multiply faster than human operators can review them. The result is shadow AI by default, because access exists outside a centrally managed discovery and approval process.

Practical implication: treat unmanaged agent-to-tool connections as lifecycle debt, not just integration clutter.

Why enterprise registries need environment separation and auditability

Enterprise MCP registries extend the open specification with access control, environment separation, allowlisting, and audit trails. Those controls matter because development, staging, and production tools cannot be governed as one flat catalog. A registry that cannot show who published a server, which agents can discover it, and where it is allowed to run leaves the organisation unable to prove control over non-human access. That is a governance failure, not a usability gap.

Practical implication: require per-environment visibility and auditability before allowing agents to discover production tools.

NHI Mgmt Group analysis

Registry sprawl is becoming the new identity sprawl for AI agents. The same control failure that once produced unmanaged API sprawl now appears in MCP tool discovery. When every agent can discover tools through isolated configs, no one can reliably answer which identity reached which service, under what policy, or across which environment. That turns discovery into a governance problem, not an inventory problem. Practitioners should treat registry design as part of the identity control plane.

Discovery without enforcement creates a false sense of control. A registry can centralize metadata, but it does not stop an agent from using a server once the connection details are known. That means the governance boundary must extend from catalog approval to runtime authorization, logging, and revocation. The field should stop describing registries as the answer on their own, because they are only one half of the decision path.

Shadow AI now begins at tool discovery, not only at model usage. Agents that query a registry at runtime can expand access faster than human review cycles can track. That shifts the identity challenge from static provisioning to discovery governance, especially where production tools, credentials, and AI workflows converge. Practitioners need to reframe discovery as an access event that deserves policy, not just as a lookup.

MCP registry governance is an NHI lifecycle problem in disguise. The registry publishes, discovers, and consumes machine-accessible endpoints, which means every entry has an implied onboarding, review, and offboarding lifecycle. If a server is retired, compromised, or moved between environments, the catalog has to reflect that state immediately or it becomes a stale access source. The implication is that lifecycle discipline now extends to tool directories as well as secrets and service accounts.

Identity policy for agents must be portable across discovery and enforcement layers. The most defensible model is one where approval in the registry and control in the gateway share the same trust decision. That does not mean centralising everything in one product. It means preventing policy drift between what an agent is allowed to find and what it is allowed to use. Practitioners should align registry design with governance operating model, not with convenience alone.

From our research:

• 92% agree governing AI agents is critical to enterprise security, yet only 44% have implemented any policies to do so, according to AI Agents: The New Attack Surface report.
• Only 52% of companies can track and audit the data their AI agents access, leaving 48% with a complete blind spot for compliance and breach investigation, according to AI Agents: The New Attack Surface report.
• For a practical governance baseline, review NHI Lifecycle Management Guide to map discovery, approval, and retirement across machine identities.

What this signals

MCP registries will force identity teams to extend governance from credentials to discovery surfaces. Once agents can query a directory at runtime, the catalogue itself becomes a control point that needs ownership, review cadence, and revocation discipline. The programme risk is not only unauthorized access. It is stale discovery paths that keep exposing retired or over-permissioned tools.

Our view is that registry maturity will be judged by whether it reduces discovery sprawl, not by whether it adds another index. Enterprises should expect the effective model to pair catalog governance with runtime enforcement and audit evidence. That is the difference between a searchable list of tools and a defensible identity boundary for agents.

With 80% of organisations reporting AI agents have already acted beyond intended scope in our research, the probability of unmanaged tool discovery is no longer hypothetical. The practical response is to align registry policy with NHI lifecycle control and then validate it against OWASP Agentic Applications Top 10 so discovery, privilege, and runtime use are assessed together.

For practitioners

• Define registry ownership and approval rules Establish who can publish MCP servers, who can approve entries, and what metadata is mandatory before discovery is allowed. Require ownership, environment, and authentication fields for every registered server.
• Bind discovery to runtime enforcement Connect the registry to an MCP gateway or equivalent enforcement layer so approved discovery does not become uncontrolled access. Use shared identity, policy, and audit context across both layers.
• Separate environments in the catalog Prevent development agents from discovering production tools unless access is explicitly authorised. Keep environment-specific registries or strict visibility partitions so tool exposure matches operational risk.
• Track registry entries through lifecycle events Treat onboarding, change, retirement, and revocation as lifecycle events for MCP servers. Remove stale entries quickly when tools move, are decommissioned, or no longer meet policy.

Key takeaways

• MCP registries centralize tool discovery for AI agents, which makes them a governance control point rather than just an architectural convenience.
• Without runtime enforcement, auditability, and environment separation, registries can turn agent access into shadow AI with faster sprawl and weaker accountability.
• Identity teams should manage MCP registries as part of the NHI lifecycle, linking discovery approval to policy, revocation, and runtime control.

Key terms

• MCP Registry: A central directory that stores metadata about MCP servers so AI agents can discover tools, endpoints, and authentication requirements. It does not host the tools themselves. In practice, it becomes an identity-adjacent control point because discovery determines what machine consumers can reach.
• MCP Gateway: A runtime enforcement layer that sits between an AI agent and an MCP server. It checks authorization, applies policy, and can add logging or rate limits before the request reaches the tool. Unlike a registry, it controls use rather than discovery.
• Shadow AI: Unmanaged AI agents or AI-driven workflows that exist outside formal visibility and governance. In an MCP context, shadow AI appears when agents discover and connect to tools without central approval, audit trails, or lifecycle oversight.
• Environment Separation: The practice of keeping development, staging, and production access distinct so a machine identity cannot discover or use higher-risk tools by default. For AI agents, environment separation is a practical boundary that prevents a single catalog from flattening risk across systems.

Deepen your knowledge

NHI governance, agentic AI identity, and machine identity security are core topics in our NHI Foundation Level course, the industry's only accredited NHI security programme. If you are responsible for identity security strategy or governance in your organisation, it is worth exploring.

This post draws on content published by Kong: What is an MCP Registry? The Centralized Directory for AI Agents. Read the original.