They should classify MCP servers as governed access paths, assign ownership, and review the systems each server can reach. Untracked connectors often become shadow AI infrastructure, which means security and IAM teams need an approval and inventory model before those paths multiply further.
Why This Matters for Security Teams
mcp server are not just integration helpers; they are governed access paths into systems, data, and tools. When each project can stand up its own server, access expands faster than review, and ownership becomes unclear. That creates shadow AI infrastructure, where a connector looks temporary but behaves like a durable privilege path. Current guidance from the OWASP Agentic AI Top 10 and NHIMG research on mcp security both point to the same issue: ungoverned tool access is the risk, not the protocol itself.
That matters because MCP servers often bridge into SaaS, internal APIs, code repos, ticketing systems, and secrets stores. If those paths are not inventoried, teams lose the ability to answer basic questions such as who approved the server, what it can reach, and whether its permissions still match the project’s actual need. In practice, many security teams encounter over-permissioned MCP exposure only after sensitive data has already been traversed through an unmanaged connector, rather than through intentional architecture review.
How It Works in Practice
The practical response is to treat every MCP server as a first-class identity boundary, not a convenience endpoint. That means assigning an owner, registering the server in an inventory, mapping every downstream system it can access, and requiring review before new tool permissions are added. Where teams already use IAM or PAM, the server should inherit the same governance expectations as any other privileged integration. The State of MCP Server Security 2025 from Astrix Security is a useful benchmark here because it shows how quickly exposed secrets and weak scoping accumulate once MCP deployments spread across teams.
For implementation, security teams should separate three layers:
Server identity: which project owns the MCP server, and who can change its configuration?
Tool scope: which actions the server may perform, ideally with explicit allowlists rather than broad access.
Downstream reach: which systems, datasets, and secrets the server can touch, including indirect access through chained tools.
That inventory should feed approval workflow, periodic recertification, and log review. If the server is used by agents or other automated workloads, the governance bar should be higher because those consumers can execute rapidly and in unexpected sequences. NHIMG’s OWASP Agentic Applications Top 10 analysis reinforces why runtime tool access needs explicit control, not trust by default. These controls tend to break down when teams allow every project to mint its own connector against production systems because no single owner remains accountable for drift.
Common Variations and Edge Cases
Tighter MCP governance often slows project velocity at first, so organisations must balance developer convenience against the risk of uncontrolled access sprawl. The right answer is not to block all new servers, but to apply tiered review based on data sensitivity, system criticality, and whether the server can modify state or only read from it. Best practice is evolving here, and there is no universal standard yet for MCP lifecycle governance, especially in multi-team platform environments.
Edge cases show up when teams share one MCP server across many projects, when a server is embedded inside a developer workstation, or when the server is managed outside the central platform team. Those patterns can make ownership ambiguous and auditing incomplete. In those environments, a simple approval list is not enough; teams need explicit naming, scoped credentials, short-lived access where possible, and a rule that any server touching production or secrets must be reviewed as privileged infrastructure. The same logic applies when MCP is used to accelerate coding assistants, because the server may become the real control point behind the agent’s behavior.
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 | MCP sprawl creates unmanaged tool access for agents and assistants. |
| CSA MAESTRO | I2 | MAESTRO addresses agent tool governance and access boundaries. |
| NIST AI RMF | GOVERN | AI RMF governance is needed to assign accountability for autonomous access paths. |
Treat each MCP server as governed agent infrastructure with explicit ownership and approval.
Related resources from NHI Mgmt Group
- How should security teams make NHI best practices usable across the business?
- How should security teams implement policy as code across Kubernetes and Terraform?
- How should security teams govern AI workloads across multiple cloud providers?
- How should security teams prioritise NHI remediation in cloud environments?
Deepen Your Knowledge
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
