Agentic AI Infrastructure
MCP Server Production Readiness
A validation track to evaluate authentication, authorization, tool-level permissions, audit logging, reliability, observability, and operational readiness of MCP server deployments.
Executive summary
This draft evaluates the production readiness of MCP (Model Context Protocol) server deployments used to expose tools and context to AI agents. No verdict has been issued; testing is in progress.
Scope
MCP server implementations used to mediate tool access between agents and backend systems.
Assumptions
Deployments run in a networked environment with multiple tenants or agents able to reach the server.
Production questions being tested
How is authentication enforced? Are tool-level permissions scoped per caller? How are secrets handled? What audit trail exists for tool invocations?
Sandbox architecture
Sandbox architecture placeholder — reference deployment to be documented as testing proceeds.
Review areas
Security
Planned: authentication, authorization, tool-level permissions, secret handling, prompt injection risk, tool misuse risk.
Reliability
Planned: failure handling, retry behavior, timeout behavior, rate limiting.
Observability
Planned: audit logging, tracing of tool calls, error visibility.
Operations
Planned: deployment model, upgrade and rollback, multi-tenant risk, data exposure risk.
Final recommendation not yet available
This report has not completed peer review and public comment.
No reviewer conflicts declared. Reviewer assignment pending.
Findings
No findings submitted yet
Contributors can submit findings from the Submit a Finding workflow.
Review status
No reviewers assigned yet