A
licenseA
qualityC
maintenanceRuntime policy enforcement for AI agents. Evaluate every agent action against your organization's policies before execution, with observe and enforce modes.
1
1
MIT
UNITARES
by cirwel
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@vorionsys/mcp-serverofficial
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TDQS
A4.1/5.0
Scored across 13 tools
Disambiguation3/5
Core tools target distinct governance actions, but several boundaries overlap: start_session vs identity, sync_state vs check_working_state vs record_result, and consult vs request_review can be confused. The verbose descriptions help clarify intended use, but an agent must read carefully to avoid misselection.
Naming Consistency3/5
All names use snake_case, but the convention is mixed between verb_noun phrases (search_shared_memory, start_session) and bare nouns or verbs (identity, self_recovery, consult). It remains readable, but it is not a predictable verb_noun pattern throughout.
Tool Count5/5
The 13 tools fit the governance/identity/knowledge-graph scope well and stay within a reasonable range. Each tool covers a distinct capability area, including discovery gateway tools needed for progressive advertisement.
Completeness4/5
The surface covers session/identity, state checks, findings, results, reviews, recovery, and progressive discovery via list_tools/describe_tool/use_tool. Some important operations such as update_finding and operator_resume_agent are only reachable indirectly through the gateway, which is workable but adds friction.
Maintenance
ActivityActive
ResponsivenessResponsive