Archestra is an enterprise platform for managing and securing Model Context Protocol (MCP) servers and AI agents in organizational environments. Core capabilities include: Security & Guardrails: - Deterministic guardrails designed to prevent data exfiltration by AI agents - Addresses the "Lethal Trifecta" vulnerability: agents with simultaneous access to private data, untrusted content processing, and external communication - Blocks prompt injection attacks that could cause agents to leak sensitive data or corrupt systems - Tool call blocking with tracking of blocked events Private MCP Registry: - Centralized registry for managing self-hosted, remote, self-built, and third-party MCP servers - Version control with rollback capabilities - Granular, team-based access control and permissions - Compliance and governance enforcement across deployments User Interface & Access: - ChatGPT-style chat interface for technical and non-technical users - Company-wide prompt library for sharing prompts across teams - One-click connection to approved MCP servers - Multi-model support (Claude, GPT-4, Gemini, open-source models) - Agent interaction via Slack, Microsoft Teams, and email Infrastructure & Orchestration: - Kubernetes-native MCP orchestrator with enterprise-grade isolation - Secrets management, audit trails, and centralized governance - Auto-scaling with health checks - Terraform provider and Helm chart for Infrastructure as Code deployments Cost Management: - Per-team, per-agent, and per-organization token usage and cost monitoring - Dynamic model switching to reduce costs (up to 96% reduction claimed) - Granular budget limits and tool call/result compression Observability: - Prometheus metrics export - OpenTelemetry distributed tracing - Pre-configured Grafana dashboards - LLM performance metrics (time to first token, tokens per second)