What you get
Python SDK
- Instrumentation:
@guarded_actiondecorator for automatic telemetry - Policy enforcement: Budgets, allow/deny lists, rate limits
- Human-in-the-loop: Approval workflows for sensitive actions
- Intervention tracking: See what Sentinel blocks and why
- Remote sync: Background sync to platform
- Replay mode: Zero-cost deterministic replay for debugging
- LLM integrations: Transparent instrumentation for OpenAI, Anthropic, Grok, Gemini
- Framework support: Native LangChain and CrewAI integrations
- MCP client: Model Context Protocol for LLM-platform interaction
- Error handling: Comprehensive error types with recovery strategies
Platform
- Agent discovery: Automatic registration and metrics
- Interventions: Track policy enforcement and cost prevention
- Approvals: Human-in-the-loop approval workflows
- Activity Ledger: Complete audit trail with advanced filtering
- WebSocket real-time: Live event streaming
- MCP endpoints: LLM-native API for autonomous operations
- Stats & analytics: Cost tracking and performance metrics
- Replay analysis: Determinism scoring and divergence detection
- Compliance: EU AI Act Article 14 support
Web Console
- Real-time dashboard: Live monitoring with WebSocket updates
- Interventions page: Policy enforcement visibility
- Approvals inbox: Review and approve sensitive actions
- Runs explorer: Execution history with replay simulation
- Activity Ledger: Complete audit trail with export
- Agent management: Fleet overview with performance metrics
- Analytics: Cost dashboards and optimization recommendations
- Settings: Policy builder, API key management, notifications
Quickstart
Get started in 10 minutes - instrument your agent and sync to the platform.
Python SDK
Full SDK documentation - instrumentation, policies, approvals, LLM integrations.
Platform API
Platform documentation - agents, interventions, approvals, real-time updates.
Web Console
Web UI guide - dashboard, interventions, approvals, runs, analytics.
How Agent Sentinel fits into your agent
At runtime your agent code calls tools / functions. Agent Sentinel wraps those calls:- Before execution: policy engine checks allow/deny lists, budgets, and rate limits.
- After execution: a ledger entry is appended (inputs, outputs, cost, duration, outcome).
- Optional: a background sync thread batches ledger entries to the platform (
/api/v1/ingest/).
Key features
Interventions
Track what Agent Sentinel blocks and demonstrate platform value.
Approvals
Human-in-the-loop approval workflows for sensitive actions.
LLM integrations
Transparent instrumentation for OpenAI, Anthropic, Grok, Gemini.
Agent discovery
Automatic agent registration with performance metrics.
Real-time updates
WebSocket event streaming for live dashboard updates.
Web console
Modern web UI for monitoring, approvals, and analytics.
Core concepts
Actions & runs
The core data model: runs contain actions; actions have cost and outcome.
Policies
Budgets, allow/deny lists, rate limits, and remote policy sync.
Activity Ledger
Complete audit trail with compliance metadata and export.
Agent Sentinel is fail-open for telemetry (ledger writes and sync should never crash your agent), but policy enforcement is fail-closed by design (violations raise).
