Now available as an MCP server for Claude

Runtime AI workload security,
just ask Claude.

What we DeliveR

What RoonCyber.AI tells Claude

Ask once, get the full picture — exposure risk, data egress paths, and a step-by-step remediation roadmap.
Exposure risk quantified
See dollar-range estimates of your AI data exposure across every mission-critical app — broken down by application, data type, and egress destination.
Four-phase remediation plan
From 48-hour hardening to long-term zero-trust AI governance — Claude generates a concrete roadmap with timelines, prioritized by severity.
Works with Claude Opus
Leverages Claude's reasoning capabilities to synthesize raw telemetry into plain-language executive summaries and actionable remediation steps.
No new dashboards
Runs entirely inside Claude via MCP. Ask in plain English, get structured analysis. No setup beyond connecting the server.
Real-time workload visibility
Monitors AI workload activity across your production environment and surfaces anomalies, privilege escalations, and policy violations as they happen.
Line-item CISO dashboard
Claude surfaces risk scores, data pathways (secrets, PII, financial records), and exposure to providers like Anthropic, Bedrock, and OpenAI in a single table.
Easy to Connect

Three steps to full visibility

01.
AI Privileged
Access
AI agents increasingly operate as automation systems with access to APIs, cloud services, internal applications, and sensitive data. If manipulated or compromised, attackers may indirectly access infrastructure and critical systems through those agents — creating new pathways into cloud environments.
02.
Visibility Lost at the Prompt
Most AI security tools focus on prompt injection detection, model safety, and LLM guardrails. While these approaches analyze text interactions with models, they rarely reveal what actually happens when AI systems execute actions across production infrastructure.
03.
Runtime Blind Spots in the Cloud
To truly secure AI workloads, organizations must understand how AI interacts with cloud infrastructure. Without runtime visibility, security teams cannot see how AI-driven activity moves across services, APIs, and data stores or understand the potential impact on critical systems.
Step 1

Connect the MCP server

Add the RoonCyber.AI MCP server to Claude in under five minutes. No agents, no infrastructure changes required.
Step 2

Ask Claude a question

Type a plain-English prompt — "What are our top AI security risks this week?" — and Claude does the rest.
Step 3

Get a CISO-ready report

Claude returns scored risk analysis, data exposure pathways, estimated financial impact, and a prioritized remediation roadmap.