Accountability should sit with the teams that own identity governance, platform engineering, and security policy. They need to define which servers are approved, who can see them, and how installation is validated. If registry policy is left informal, organisations usually end up with inconsistent access, weak oversight, and unmanaged agent-tool relationships.
Why This Matters for Security Teams
MCP registry policy is not a cataloging exercise. It is the control point that determines which tools, servers, and integrations an AI agent can discover and invoke. When ownership is unclear, approvals become inconsistent, access reviews miss tool-level risk, and security teams lose visibility into which identities are binding to which capabilities. That creates a governance gap across identity, platform, and application security.
This is especially important in agentic environments because agents do not behave like static human users. They can chain tools, retry actions, and expand their reach faster than a manual approval process can keep up. NHI Management Group’s research on AI Agents: The New Attack Surface report shows that 80% of organisations report agent actions beyond intended scope, including unauthorised system access and credential exposure. That is a policy ownership problem as much as a technical one.
The governance question also maps directly to recognised controls in OWASP Non-Human Identity Top 10 and the NIST Cybersecurity Framework 2.0, both of which emphasise accountable access control and lifecycle discipline for machine identities. In practice, many security teams only discover MCP registry drift after an agent has already connected to an unreviewed server.
How It Works in Practice
Accountability should be split by function, but not diffused. Identity governance should own who is allowed to approve registry entries and what assurance is required before an MCP server becomes discoverable. Platform engineering should own the operational registry, server registration workflow, and validation of installation artifacts. Security policy teams should define the minimum control set for approval, logging, revocation, and periodic review. That separation keeps policy design, technical enforcement, and operational execution aligned.
In mature environments, the registry is treated as an enforcement surface, not documentation. Approval criteria should include server provenance, intended tool scope, secret handling, data access boundaries, and the identity of the workload or agent that will use it. Where possible, teams should require short-lived credentials, explicit access scoping, and runtime policy checks rather than relying on static allowlists. Guidance from the OWASP Top 10 for Agentic Applications 2026 supports this direction because autonomous systems can change behaviour after initial approval.
NHI Management Group’s Ultimate Guide to NHIs — Lifecycle Processes for Managing NHIs reinforces the need for ownership across provisioning, review, and revocation. The same logic applies to MCP registries: approvals should be traceable, time-bound where possible, and linked to a named control owner who can answer why the server exists and who can use it. A registry that cannot produce an approver, a rationale, and an expiry path is not governed. These controls tend to break down in fast-moving developer environments because local teams bypass the registry to avoid release friction.
Common Variations and Edge Cases
Tighter registry control often increases delivery overhead, requiring organisations to balance faster agent experimentation against stronger assurance. That tradeoff is real, especially when product teams need frequent tool onboarding or when MCP servers are maintained by multiple engineering groups.
Current guidance suggests a tiered model: low-risk internal tools can move through a lighter review, while servers exposing sensitive data, write actions, or privileged system commands need formal approval from identity governance and security. There is no universal standard for this yet, but the direction is clear: higher blast radius demands stronger ownership and evidence. This aligns with findings in the The State of MCP Server Security 2025, which reports that only 18% of MCP server deployments implement access scoping and 53% expose credentials through hard-coded values.
Edge cases arise when third-party teams host MCP servers, when a single registry feeds multiple agent frameworks, or when agents are allowed to self-select tools at runtime. In those cases, accountability should remain with the enterprise control owner, even if implementation is delegated. Security teams should also ensure that monitoring can distinguish approved tool use from unexpected chaining or lateral movement, a concern echoed in Top 10 NHI Issues. When this fails, organisations usually inherit shadow tool access before they notice the registry was never acting as a real control.
Standards & Framework Alignment
This section maps relevant standards and security frameworks to the operational risks and controls described in this guidance.
OWASP Agentic AI Top 10, OWASP Non-Human Identity Top 10 and CSA MAESTRO address the attack and risk surface, while NIST AI RMF and NIST CSF 2.0 set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP Agentic AI Top 10 | A2 | Covers tool misuse and agent-driven access expansion through unmanaged integrations. |
| OWASP Non-Human Identity Top 10 | NHI-03 | Registry policy depends on lifecycle control for non-human identities and their secrets. |
| CSA MAESTRO | TRUST-03 | Maestro emphasises trust, policy, and governance for agentic system access. |
| NIST AI RMF | AI RMF governs accountability and oversight for autonomous AI-enabled access decisions. | |
| NIST CSF 2.0 | PR.AC-4 | Access permissions should be managed with least privilege and clear authorization. |
Define accountable owners for MCP policy, review exceptions, and document decision rationale.
Related resources from NHI Mgmt Group
- Who should be accountable for approving access requests in a policy-driven model?
- Who is accountable when authorization decisions cannot be traced back to the policy version that made them?
- Who is accountable when access decisions, application ownership, or documentation are incomplete?
- Who is accountable when access decisions rely on AI-powered risk scoring and a user is incorrectly blocked or challenged?