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Monitor AI agents with policy enforcement, audit logs, and risk blocking via Splunk MCP.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "AgentGuard for Splunk MCP" yet — see the docs or source repo.
Design a safety policy set for an AI agent using Splunk MCP: log all tool calls, restrict deletion of production resources, and immediately block and alert on high-risk commands.
A practical agent safety policy plan with audit rules, blocking conditions, and alert workflows.
Analyze the AI agent's tool call logs from the last 24 hours, identify unusual frequency, failed actions, and possible policy violations, then summarize them by risk level.
An audit summary listing anomalous calls, potential policy violations, and their risk ratings.
Create rules for an AI agent so that bulk deletions, privilege escalation, or access to sensitive systems are blocked first, require human approval, and preserve full evidence trails.
A high-risk action blocking and human approval workflow with evidence retention requirements.
Investigate Splunk exports or live queries locally for security and ops insights.
Audit MCP servers and AI packages for security and supply chain risks.
Enforce permissions, approvals, sanitization, and audit for AI agent MCP calls.
Investigate agents, conversation threads, and content trust signals for analysis.
Protect MCP-connected agents with PII redaction, rate limits, and policy enforcement.
Securely run agent tools with isolation, permissions, and centralized MCP registry.