Yes. Centralised access control gives teams one place to approve scopes, one place to revoke risky connections, and one audit trail for connected tools. Without that, every employee-managed grant becomes a separate trust decision that is hard to inventory and harder to unwind when a third party is compromised.
Why Centralising AI Tool Access Changes the Security Model
Centralisation turns AI tool access from a series of local approvals into a governed control point. That matters because MCP integrations often connect agents to data, systems, and actions with durable permissions. A central model makes approval, review, and revocation consistent, and it prevents every user or team from inventing its own trust path.
It also changes how organisations think about blast radius. If one integration is risky, you want to know exactly which connected tools depend on it, what scopes were granted, and whether those scopes can be narrowed without breaking core workflows. Centralisation is not just administrative convenience, it is an access design choice that affects containment.
For teams evaluating MCP specifically, the control question is whether the gateway or registry becomes the policy boundary. When it does, the organisation can require the same standards for token handling, scope limits, and tool onboarding across all integrations instead of relying on inconsistent employee-by-employee decisions. That is why the central point of control should be explicit rather than accidental.
What Centralisation Gives You That Distributed Grants Do Not
A central approval model gives you one place to enforce tool-level policy, one place to record what was connected, and one place to remove access when a tool is no longer needed. That is especially useful when an AI workflow touches multiple services, because distributed grants tend to accumulate quietly and outlive the original business need.
It also improves inventory quality. Centralised management creates a clearer view of which tools have access, whether they are first-party or third-party, and which users or agents are relying on them. Without that inventory, organisations usually discover integrations only after an outage, a security review, or a compromise in the supplier chain.
The best central models do not just collect approvals, they also separate authentication from authorisation. A tool may be technically able to authenticate, but that does not mean it should have broad runtime access. The MCP authorization specification reflects this distinction by treating servers as resource servers and binding access to audience-limited tokens rather than open-ended passthrough.
How to Decide Whether More MCP Integrations Are Safe to Add
The practical test is whether each new integration can be governed under the same review, revocation, and logging model as the rest of the tool estate. If the answer is no, the organisation is not really adding integrations, it is adding unmanaged trust relationships. That becomes harder to defend as the number of connected tools grows.
Centralisation is most valuable when the organisation can pair it with identity-aware review. That means reviewing who approved the connection, what data the tool can reach, whether the access is time-bounded, and whether the integration can be removed without manual clean-up in every employee account. The control should make risky grants easy to find and easy to unwind.
For practitioners, the right sequence is to standardise the access path first, then expand the catalogue of approved MCP tools. If you add integrations before the boundary is defined, you will spend the next quarter trying to recover visibility from dozens of local exceptions. MCP Security Guide is useful here because it frames the authorisation model, gateway pattern, and token-handling decisions that make central governance practical.
Risk and Threat Considerations
Distributed AI tool grants create a wider attack surface because every local approval can become a separate trust dependency. If one third-party tool, connector, or token-handling path is compromised, the organisation may have many more affected grants than it can see quickly, and revocation becomes slow precisely when speed matters most.
Failure mechanism: Access is approved and stored in multiple places, so revocation, inventory, and scope review drift apart. That makes it easier for overbroad or stale grants to persist, and it gives a compromised tool more chances to reuse trust that was approved for a different context.
Impact: A single compromise can spread into multiple downstream systems, especially when tool connections are allowed to inherit user-level trust or long-lived credentials. In practice, that can mean unauthorized data access, hidden persistence, and slower containment after a supplier or integration failure.
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 and OWASP Non-Human Identity Top 10 address the attack and risk surface, while NIST SP 800-53 Rev 5 and CIS Controls v8 set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP Agentic AI Top 10 | ASI03 — Identity & Privilege Abuse | Centralised MCP access limits agent and tool privilege sprawl. |
| ASI02 — Tool Misuse | MCP integrations expand tool use, so central approval reduces misuse risk. | |
| Recommendation — Enforce one governed approval point for tool scopes and revocation. Restrict approved tools and validate each new integration before enablement. | ||
| OWASP Non-Human Identity Top 10 | NHI-05 — Overprivileged NHI | MCP connections often rely on non-human credentials that need scope control. |
| Recommendation — Apply least privilege to integration credentials and remove excess scopes. | ||
| NIST SP 800-53 Rev 5 | AC-6 — Least Privilege | Centralising access enforces minimal permissions for connected tools. |
| AU-2 — Audit Events | A central model creates a single audit trail for tool approvals and use. | |
| Recommendation — Limit each integration to the minimum permissions required. Log approval, scope change, and revocation events for every integration. | ||
| CIS Controls v8 | CIS-5 — Account Management | Central management is needed to inventory and remove risky tool grants. |
| Recommendation — Maintain a complete inventory of connected tools and retire stale grants. | ||
Practitioner Guidance
What to prioritise: Treat the access boundary as the first control to build, not the last one to tidy up. If you cannot revoke an integration centrally within minutes, it is not ready for broad rollout.
What to verify: Confirm that every MCP connection is tied to an owner, a scope, an expiry or review date, and a revocation path that does not depend on each employee remembering to clean up their own grants. That evidence should be visible in one audit trail, not scattered across teams.
Common mistake: Teams often focus on whether a tool is useful and overlook whether its permissions are governable at scale. Utility is not the same as operability, and an integration that cannot be cleanly unwound is a governance problem even if it works technically.
Practitioner takeaway: Centralise first when the integration model is still expanding, because the cost of retrofitting visibility and revocation is always lower before local exceptions become embedded business dependencies.
Related resources from NHI Mgmt Group
- What should organisations do before letting an AI tool write access rules?
- Should organisations prioritise prompt inspection and MCP governance before expanding AI agent access?
- What should organisations evaluate before allowing AI agents to manage secrets, roles, and access requests?
- How should security teams govern API keys used for generative AI access?