Pebblo Safe Agent is a security product designed to govern AI agents operating over Model Context Protocol (MCP) environments. MCP servers aggregate data from various sources — tickets, documents, messages, databases, and SaaS APIs — into a unified context stream that AI agents reason over and act upon. Pebblo Safe Agent addresses the security risks introduced by this architecture, where context itself becomes executable and can influence agent behavior. The product is structured around three core security pillars: 1. Context Integrity — Detects and prevents prompt injection attacks where malicious instructions are embedded within seemingly normal data (e.g., a Jira ticket containing hidden commands). The agent enforces prompt and instruction sanitization, runtime intent validation, and inline blocking with audit logging. 2. Data Protection — Prevents unauthorized data access and leakage by AI agents. Agents that optimize for task completion may inadvertently collect or share sensitive data, including PII or confidential documents, beyond their entitlements. Pebblo Safe Agent enforces data access controls to limit over-collection and over-sharing. 3. Behavioral Governance — Detects unsafe or anomalous agent behavior in real time, addressing scenarios where static rules are insufficient to govern dynamic agent actions. The product targets production AI agent deployments and is positioned for regulated industries where data sensitivity and compliance requirements demand runtime oversight of agentic workflows.