Treat runtime context requests as a controlled identity interaction, not a convenience feature. Define which servers may elicit input, require explicit user approval for any state-changing branch, validate every response against schema, and log the requesting server identity. If the request could expose secrets or PII, it should move to a separate secure channel rather than remain in the MCP flow.
Why This Matters for Security Teams
Runtime context requests in MCP are not just prompt-handling events. They are moments when an upstream server tries to shape what the agent sees, what it asks for, and potentially what it can do next. That makes them an identity and authorization problem, not a UX detail. Current guidance suggests treating each request as a governed interaction with explicit provenance, policy checks, and a clear boundary between benign context and data exposure.
This matters because MCP environments are already showing the same control gaps seen in broader NHI programs. NHIMG’s State of MCP Server Security 2025 found that only 18% of deployments implement any access scoping for tool permissions, while 53% expose credentials through hard-coded configuration values. In that environment, a runtime context request can become an easy path from harmless-looking metadata into sensitive state.
Security teams often underestimate how quickly an agentic workflow can pivot once a server can influence context, request branching, or downstream tool use. In practice, many teams discover the risk only after a server-side prompt has already expanded access or exposed secrets, rather than through intentional design review.
How It Works in Practice
The safest pattern is to govern runtime context requests as a controlled trust handshake between the MCP server, the agent runtime, and the user. The server identity should be explicit, the request purpose should be machine-readable, and the response path should be constrained by policy before any data is returned. That aligns with the direction of the OWASP Agentic AI Top 10 and the NIST Cybersecurity Framework 2.0, both of which emphasize governance, traceability, and controlled access rather than blind runtime trust.
In practice, security teams should require four checks:
- Authenticate the requesting server and bind the request to a known workload identity.
- Classify the request as read-only, state-changing, or sensitive, then gate each class differently.
- Validate every response against schema and expected value ranges before it reaches the agent.
- Log the server identity, the requested context, the policy decision, and the user approval state.
If the request could reveal secrets, tokens, or PII, the better design is to move that exchange into a separate secure channel with explicit consent and tighter retention rules. That reduces the chance that a generic MCP flow becomes an exfiltration path. NHIMG’s Top 10 NHI Issues is useful here because it frames the recurring failures around weak governance, poor lifecycle control, and missing visibility.
These controls tend to break down when MCP servers are dynamically discovered, unauthenticated, or allowed to chain into other tools without per-request policy evaluation.
Common Variations and Edge Cases
Tighter runtime controls often increase friction, so organisations have to balance agent usefulness against the operational cost of approvals and logging. There is no universal standard for this yet, especially for long-running conversations where the agent needs multiple context refreshes from different servers.
One common edge case is low-risk context that becomes high-risk after a later tool call. Best practice is evolving toward contextual authorization: approve the request based on the agent’s current intent, the server’s trust level, and the sensitivity of the downstream action, not just the initial prompt. That is especially important in workflows where a server can influence tool selection or inject instructions that change the agent’s behaviour mid-session.
Another edge case is when the runtime context request includes secrets that are only needed briefly. Static credentials are a poor fit for this pattern; short-lived, purpose-bound access is safer, but the control should still be explicit. For lifecycle and audit alignment, NHIMG’s Ultimate Guide to NHIs — Lifecycle Processes for Managing NHIs and Ultimate Guide to NHIs — Regulatory and Audit Perspectives reinforce the need for traceability, reviewability, and explicit ownership. If the environment cannot reliably distinguish benign from sensitive requests, the flow should be split rather than expanded.
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 | A1 | Runtime context requests can steer agent behaviour and tool use. |
| CSA MAESTRO | GOV-2 | Governing agent-server interactions needs explicit trust and policy control. |
| NIST AI RMF | AI RMF applies to runtime decisions that can alter agent risk and impact. |
Classify each request by intent, validate outputs, and block unsafe branching before the agent acts.
Related resources from NHI Mgmt Group
Deepen Your Knowledge
Reviewed and updated by the NHIMG editorial team on June 8, 2026.
NHI Mgmt Group — the #1 independent authority on Non-Human Identity, IAM, and Agentic AI security. nhimg.org
