TL;DR: Public MCP registries solve discovery but not the production controls enterprises need, according to MintMCP’s analysis, because authentication, authorization, audit trails, and runtime policy enforcement must still be added around the protocol. The central governance gap is that catalog visibility does not equal governed access, especially when AI agents connect to business systems at scale.
At a glance
What this is: This is an analysis of why MCP registries are useful for discovery but insufficient as enterprise control points when AI agents need governed access to production systems.
Why it matters: IAM, NHI, and AI governance teams need a registry model that separates finding tools from authorising them, because auditability and runtime enforcement matter once agents touch real data and systems.
By the numbers:
- The protocol also reached 97 million monthly SDK downloads, underscoring the pace of adoption across agent and tool integrations.
Context
MCP registries are discovery layers, not governance layers. They help AI clients and developers find servers, but they do not by themselves enforce who can use a server, what credentials are allowed, or whether tool calls are logged for audit and compliance.
The governance gap becomes sharper as enterprises move from experimentation to production. Public discovery is enough for prototyping, but organisations operating regulated data or high-risk workflows need runtime enforcement and gateway control that sits between the client and the server.
Key questions
Q: What breaks when an MCP registry is used as the only control layer?
A: Discovery still works, but access control, credential governance, and auditability do not. Teams end up with visibility into what exists while missing proof of who accessed which tool, under what permissions, and whether the action was policy compliant. That leaves production deployments exposed even when the registry looks well managed.
Q: Why do public MCP registries create governance risk in production?
A: Because discovery does not answer the operational questions that matter in production: who may connect, which credentials are permitted, what each tool can do, and how the access is recorded. Without those controls, a registry can expand adoption while leaving the actual execution path under-governed.
Q: How should security teams govern AI agent identities in MCP workflows?
A: Treat each agent as a governed non-human identity with an owner, task scope, expiry window, and revocation path. The key control is not just authentication at start-up, but continuous authorization at tool boundaries so the agent cannot expand its own effective privilege through chained actions.
Q: What do security teams need to verify before exposing an MCP server to users?
A: Teams need to verify who can register as a client, what scopes they can request, how tokens are validated, and how consent maps to real tool permissions. If any of those links are vague, the MCP server can expand access beyond the user’s intent or the organisation’s policy. Auditability should be built in before go-live.
Technical breakdown
Why discovery registries stop short of production control
An MCP registry is a catalogue of servers and their advertised capabilities, not a policy engine. Discovery helps agents locate tools, but it does not authenticate the caller, enforce authorisation, or record the tool invocation in a way that supports compliance review. That separation matters because production risk sits in use, not just in visibility. A registry can tell you a server exists, but it cannot on its own answer whether a specific user, agent, or session should be allowed to reach it. Practical implication: treat registry data as inventory, not as access control. See the MCP Security Guide.
Practical implication: Use registry entries as the starting point for access design, not as evidence that the server is safe to expose.
Why enterprise MCP needs identity, policy, and audit together
Enterprise MCP governance combines authentication, authorisation, credential handling, and logging because those controls fail when they are separated. If server discovery sits in one system, secrets in another, and audit logs in a third, operators lose the ability to prove which identity accessed which tool under which policy. That creates a governance gap for regulated environments and for any deployment where AI agents can initiate actions on behalf of users. Practical implication: design the MCP control plane as an identity and audit layer, not as a directory only. See the NHI Authentication Guide.
Practical implication: Bind identity, permissions, and event logging into one governed path so access decisions remain reviewable.
How agent identities change MCP governance
The article’s key architectural point is that AI agents should not borrow a human’s long-lived access context. Agent identities need their own credentials, scoped permissions, and audit trails so rotation, revocation, and attribution work at the agent level rather than collapsing into shared accounts. That is an NHI pattern applied to AI systems: the governance unit is the non-human actor, not the developer or operator who created it. Practical implication: isolate agent credentials from human identities and avoid shared keys that erase accountability.
Practical implication: Assign distinct credentials and scoped access to each agent so one compromised agent does not expand the blast radius.
Threat narrative
Attacker objective: The attacker or misused agent seeks unchecked tool access, data exposure, or operational actions without traceable governance controls.
- Entry occurs when an AI client discovers an MCP server through a registry and reaches the tool surface through a loosely governed connection path.
- Credential exposure or abuse follows when secrets, OAuth context, or other credentials are handled outside a centralised control boundary.
- Escalation happens when runtime policy is weak enough that a discovered server can be used beyond its intended role or privilege scope.
- Impact is unauthorised access to enterprise systems and data without the audit trail needed to investigate or prove compliance.
Breaches seen in the wild
- Smithery.ai MCP hosting breach 2025: A Smithery.ai build flaw gave GitGuardian a live fly.io token controlling 3,000+ hosted MCP servers and the API keys their clients sent.
- Massive Docker Hub Secrets Leak: 10,000+ Docker Hub container images expose hardcoded secrets and authentication keys.
Read and download The State of NHI & AI Agent Breach Report 2026, covering 200+ breaches impacting Non-Human Identities including AI Agents.
NHI Mgmt Group analysis
Discovery is not governance: public MCP registries solve findability, but they do not solve entitlement, runtime enforcement, or auditability. That distinction matters because production risk emerges when an agent can actually invoke a tool, not when a developer can merely see that the tool exists. Enterprises that stop at discovery have not yet established who may act, under what policy, and with what evidence trail. The practical conclusion is simple: registry strategy and governance strategy are different control layers.
Per-agent identity is the governance boundary: once AI agents can reach business systems, shared human credentials stop being a defensible operating model. Agent identity needs its own authentication context, scoped permissions, and revocation path, otherwise attribution collapses and one compromised agent inherits the blast radius of a much larger environment. This is where NHI governance meets AI operations: the non-human actor becomes the unit of control, not the account that provisioned it.
Runtime controls matter more than catalog controls in regulated environments: enterprises handling sensitive data need proof of enforcement, not just a list of approved servers. SOC 2, HIPAA, and internal risk reporting all depend on whether tool calls, credential lifecycle events, and policy changes can be reconstructed after the fact. A registry without runtime evidence leaves compliance teams with metadata, not assurance. The implication is that governed access must be designed into the path of execution.
Private registry design is really about reducing operational sprawl: the article shows that the enterprise value of a private MCP registry is less about curation and more about consolidating authentication, authorisation, and logging into one governed path. That reduces the number of local configurations, inconsistent policies, and hidden access paths that appear when every team wires MCP independently. The practitioner takeaway is to treat MCP as an identity and control-plane problem, not just an integration problem.
From our research library:
- Only 5.7% of organisations have full visibility into their service accounts, according to the Ultimate Guide to NHIs.
- Read next: MCP Security Guide
What this signals
Public discovery will keep accelerating MCP adoption, but the programme risk shifts to the control plane once agents begin touching real systems. The teams that win governance maturity will distinguish catalogue visibility from execution authority and design the latter as a separate control boundary.
Registry-to-runtime gap: the central issue is not whether a server can be found, but whether the organisation can prove who accessed it, with what identity, and under which policy. That becomes the deciding factor for regulated use cases and for any environment where agent actions must be attributable.
As MCP spreads across more clients and workflows, enterprises will increasingly need a governed path for off-gateway activity, not just central discovery. The next phase of adoption is about proving that access was intentional, scoped, and reviewable, rather than merely available.
For practitioners
- Map every MCP server to an owner and access policy Inventory which servers are discoverable, which are approved for production, and which need removal or tighter scoping before agents can use them.
- Separate discovery from enforcement Keep public discovery for exploration, but require a governed gateway or equivalent control layer before any production tool call reaches enterprise systems.
- Issue per-agent credentials Assign each AI agent its own credentials and permissions so rotation, revocation, and audit attribution do not depend on a human account being reused.
- Centralise audit evidence Log tool calls, credential events, and policy changes in a form that security, audit, and compliance teams can reconstruct after the session ends.
- Vet servers before enabling production use Treat security testing, authentication checks, and scope review as prerequisites for approval, especially where untrusted or community-built servers are involved.
Key takeaways
- MCP registries improve discovery, but discovery alone does not enforce access, credential scope, or auditability.
- The protocol’s adoption has already moved fast enough that governance has to be designed around runtime control, not just catalogue hygiene.
- Enterprise teams should separate where tools are found from where tools are authorised, logged, and revoked.
Related NHI Mgmt Group resources: MCP Security Guide · Ultimate Guide to NHIs: Regulatory and Audit Perspectives · NHI Authentication Guide · Smithery.ai MCP hosting breach 2025
Standards & Framework Alignment
This section maps relevant standards and security frameworks to the operational risks and controls described in this guidance.
OWASP Non-Human Identity Top 10 and MITRE ATT&CK address the attack and risk surface, while NIST CSF 2.0 and NIST SP 800-53 Rev 5 set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP Non-Human Identity Top 10 | NHI-04 — Insecure Authentication | The article centres on MCP access paths that need stronger authentication than discovery layers provide. |
| NHI-05 — Overprivileged NHI | Agent identities and server access scopes are central to the governance model discussed here. | |
| NHI-10 — Human Use of NHI | The article highlights the risk of humans reusing or collapsing identities across agents and access paths. | |
| Recommendation — Require stronger authentication for MCP connections and do not rely on discovery lists as proof of trust. Scope each agent and MCP server relationship to the minimum access needed for the task. Prevent shared human credentials from being reused as the operating identity for agents. | ||
| NIST CSF 2.0 | PR.AA-05 — Access Permissions, Entitlements and Authorizations | The core issue is authorising MCP tool use, not just listing available servers. |
| Recommendation — Enforce permissions and authorisations before MCP tool calls reach production systems. | ||
| NIST SP 800-53 Rev 5 | IA-5 — Authenticator Management | The article explicitly addresses credential centralisation and rotation for MCP-connected services. |
| Recommendation — Manage MCP authenticators centrally and revoke stale credentials promptly. | ||
| MITRE ATT&CK | TA0006;TA0008 — Credential Access; Lateral Movement | Weakly governed MCP paths can expose credentials and enable movement into connected systems. |
| Recommendation — Detect credential exposure and constrain movement paths created by MCP integrations. | ||
Key terms
- Mcp Registry: An MCP Registry is a catalog that lists available Model Context Protocol servers, tools, and resources for AI agents to discover and use. It typically stores metadata such as endpoints, capabilities, ownership, and trust information, helping organizations govern which tools agents can access and how those connections are managed.
- Runtime Enforcement: Runtime enforcement is the practice of blocking malicious behaviour while software is running, rather than only detecting it after the fact. It monitors process activity, network actions, and privilege changes so a live attack can be interrupted at the point of execution.
- Agent Identity: An agent identity is the set of attributes, credentials and permissions assigned to an autonomous software entity. It is treated as a non-human identity because it can authenticate, act on systems and accumulate access over time, which creates governance, audit and lifecycle obligations similar to other production identities.
- Governed Gateway: A governed gateway is a controlled path through which AI tools or agents must pass before they can reach data, APIs, or external services. It provides a decision point for least privilege, redaction, logging, and policy checks that periodic review cannot reliably deliver alone.
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 building or maturing an IAM programme, it is worth exploring.
Published by the NHIMG editorial team on October 22, 2026.
NHI Mgmt Group, the independent authority on Non-Human Identity, IAM, and Agentic AI security. nhimg.org