Systemores Cloud MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| Authorization | No | Bearer token used to authenticate to the Systemores Cloud MCP Server (https://audit.systemores.com/api/mcp), e.g. "Bearer YOUR_SYSTEMORES_API_KEY". A Systemores Pro/Team API key (sys_pro_...) or a 7-day Trial Token unlocks the Pro/Team-only auditors. |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| systemores_stress_test_agentB | Exposes the target agent persona to a battery of adversarial prompts (Presses) and evaluates behavioral stability using Murray's Needs-Press diagnostic model. |
| systemores_evaluate_driftB | Simulates multiple conversational turns to evaluate agent output consistency and behavioral drift over extended interactions. |
| systemores_assess_biasB | Verifies the agent's compliance with fair-lending, fair-housing, employment non-discrimination (EEOC/SIOP/ECOA), or child-directed safety (COPPA) standards. |
| systemores_measure_dragC | Measures operational latency, response length, and execution drag parameters to analyze cognitive throughput stability within the Behavioral OS ecosystem. |
| systemores_tool_integrityB | Evaluates whether the agent's system prompt establishes the behavioral conditions for safe, reliable tool use — auditing tool selection discipline, argument construction fidelity, and failure resilience when tool returns are ambiguous or erroneous. |
| systemores_audit_tool_integrityB | Audits the structural integrity, naming conventions, schema completeness, safety annotations, and injection surface of an AI agent's exposed tool definitions. Identifies malformed schemas, privilege overreach, deceptive safety hints, duplicate names, and description quality gaps. Operates entirely offline — no external API calls required. |
| systemores_audit_agent_graphB | Statically scans multi-agent execution topologies (DAGs/meshes) using DFS algorithms to detect cyclic delegation loops and privilege escalation paths from public untrusted sub-agents to backend write/admin tools. |
| systemores_generate_cohortB | Generates statistical cohorts of synthetic user personas across enterprise operational domains with IPIP-NEO-120 30-facet psychometric profiles, demographic diversity, and prompt injection payloads. |
| systemores_inject_environment_faultA | Configures dynamic chaos injection policies for tools, mock APIs, and databases during simulations (HTTP 429 rate limits, 500 errors, timeouts, 401 unauthorized, malformed JSON). |
| systemores_analyze_trace_telemetryA | Ingests standard OpenTelemetry (OTel) trace JSON payloads to detect financial token cost burn traps (> $2.50 threshold), runtime loop deadlocks between sub-agents, and cognitive latency drag hotspots (> 3000ms). |
| systemores_export_dossierA | Aggregates findings from graph audits, synthetic cohort simulations, chaos tests, and trace analytics into formal compliance report packages for EU AI Act (EU 2024/1689), NIST AI RMF 1.0, EEOC/ECOA, and SOC 2 AI Addendums. |
| systemores_audit_turn_liveA | Performs real-time (~250ms) operational and behavioral turn auditing using Systemores System One. Computes policy compliance score, sycophancy probability, unauthorized tool scope, and returns an inline circuit-breaker action (DISPATCH, INTERCEPT, QUARANTINE, STRIP_TOOL). |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 12 tools
Most tools target distinct audit dimensions, but systemores_tool_integrity and systemores_audit_tool_integrity are easily confused: one evaluates prompt conditions for safe tool use while the other audits tool-definition schemas. systemores_measure_drag also overlaps with systemores_analyze_trace_telemetry on latency/drag detection, though descriptions help clarify the intended boundaries.
All tools use the systemores_ prefix and snake_case, with most following a predictable verb_noun pattern such as stress_test_agent, evaluate_drift, and audit_agent_graph. Minor deviations exist: systemores_tool_integrity lacks an action verb and systemores_audit_turn_live places the qualifier awkwardly.
Twelve tools is well within the appropriate range for a comprehensive AI-agent auditing platform. Each tool maps to a major capability area such as behavioral stress, drift, bias, tool integrity, graph auditing, cohort generation, chaos injection, telemetry analysis, reporting, and live auditing.
The surface covers the full auditing lifecycle: behavioral testing, compliance checks, tool/graph integrity, synthetic cohort generation, chaos fault injection, telemetry analysis, formal reporting, and real-time circuit-breaker auditing. No obvious workflow dead ends are apparent for the stated domain.