The organisation loses sight of which tools can connect AI models to data sources and action endpoints. That matters because MCP support turns an ordinary SaaS application into a possible bridge for machine-to-machine access. Without separate tracking, integration permissions and downstream scopes are reviewed too late, if at all.
Why This Matters for Security Teams
When MCP support is treated as a minor feature instead of a separate exposure, security teams miss the fact that the application has gained a machine-to-machine control plane. That changes the risk profile immediately: a normal SaaS record may now be able to reach data sources, trigger actions, and pass credentials through tool chains. The issue is not just discovery, but governance. If the app is not tracked separately, review workflows for integration scopes, data access, and revocation lag behind deployment.
This gap shows up in current guidance around agentic systems, where OWASP Agentic AI Top 10 and NHIMG research on OWASP Agentic Applications Top 10 both reinforce that tool access is part of the security boundary, not an implementation detail. In practice, this matters because MCP connections often become embedded in trusted software procurement, while the security team still sees only the parent application. One relevant data point from NHIMG research is that only 18% of mcp server deployments implement any form of access scoping for tool permissions, which means blind spots compound quickly.
In practice, many security teams encounter the impact only after an integration has already been allowed to read data or perform an action that nobody reclassified as privileged.
How It Works in Practice
Separate tracking means the organisation treats MCP capability as a distinct asset class, with its own inventory status, owner, approved tools, and review cycle. That is the practical difference between “this SaaS product exists” and “this SaaS product can now broker model access into internal systems.” Without that separation, auditors and operators tend to review the application’s baseline role, while the MCP layer quietly inherits broader access than intended.
Operationally, the cleanest approach is to bind each MCP-supported app to an explicit record that captures: which model or agent can invoke it, which tools are exposed, which data domains are reachable, and what actions are permitted. Where possible, access should be time-bound and task-bound rather than permanently enabled. Current best practice is evolving toward runtime policy checks rather than static approval alone, especially for autonomous workloads. That aligns with the direction of the OWASP Top 10 for Agentic Applications 2026, which emphasises tool misuse and indirect access paths, and NHIMG’s The State of MCP Server Security 2025, which shows how often tool permissions remain unscoped.
- Inventory the MCP-enabled app separately from the base SaaS record.
- Tag every exposed tool, connector, and action endpoint as a governed asset.
- Require a named owner for approvals, reviews, and revocation.
- Reassess scopes whenever new tools, data sources, or agents are added.
The control also benefits from correlation with identity logs, so that a connector invocation can be traced back to a specific workload identity or agent session. These controls tend to break down in environments where MCP is enabled through shadow IT, because the application owner may not realise the tool layer has become a privileged integration path.
Common Variations and Edge Cases
Tighter tracking often increases operational overhead, requiring organisations to balance faster experimentation against stronger approval discipline. That tradeoff is real in development and pilot environments, where teams may spin up MCP connections to support testing, demos, or internal automation before security review is complete. Best practice is evolving here, and there is no universal standard for this yet, but the direction is clear: temporary exceptions should still be visible, time-boxed, and assigned an owner.
Edge cases appear when a vendor delivers MCP support through a feature flag, plugin, or embedded integration rather than a standalone service. In those cases, security teams may miss the capability because the procurement record does not change even though the access model does. The same problem arises when one application exposes multiple tools with different sensitivity levels, because tracking the app alone hides the fact that only one connector may require privileged review. NHIMG’s analysis of Analysis of Claude Code Security is a useful reminder that tool-enabled software can expand the attack surface faster than traditional application governance expects, and the same pattern applies when MCP layers are not separately recorded.
For programmes already using agentic controls, the practical answer is to treat MCP support as a change in security classification, not just a product feature. That approach is especially important when AI systems are allowed to chain tools, because one overlooked connector can become the path for broader lateral access.
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 CSA MAESTRO address the attack and risk surface, while NIST AI RMF set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP Agentic AI Top 10 | A2 | Tool misuse and hidden action paths are the core MCP tracking risk. |
| CSA MAESTRO | M2 | MAESTRO covers agent-to-tool trust boundaries and authorization drift. |
| NIST AI RMF | AI RMF addresses governance and monitoring gaps for emergent AI-enabled access. |
Inventory MCP-enabled apps separately and bind each tool to explicit policy and ownership.
Related resources from NHI Mgmt Group
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Reviewed and updated by the NHIMG editorial team on June 9, 2026.
NHI Mgmt Group — the #1 independent authority on Non-Human Identity, IAM, and Agentic AI security. nhimg.org