Archestra

Archestra is an enterprise Model Context Protocol platform that secures and manages AI agents, tools, and data in production.

Archestra is an enterprise Model Context Protocol platform designed for platform teams moving AI into production. It acts as a single production layer between AI models and internal systems, providing a curated catalog of over nine hundred evaluated Model Context Protocol servers. The platform features an LLM proxy, a Model Context Protocol gateway, user identity integration with providers like Okta and Entra ID, policy enforcement, runtime credential resolution, and audit logging. It supports models from OpenAI, Anthropic, Azure OpenAI, Vertex AI, and Bedrock, alongside infrastructure tools like Kubernetes, Helm, Postgres, OpenTelemetry, Prometheus, and Grafana. It targets enterprise platform teams, engineers, and non-technical staff who need to control agent access, monitor costs, and trace requests. What sets it apart is its comprehensive approach to managing both Model Context Protocol infrastructure and agent runtimes under a unified, open-source policy and observability framework.

Archestra at a glance

Best for: Software engineer, Director
Runs on: Web, Kubernetes, Self-hosted
Pricing: AGPL-3.0 free self-hosted plan with all features for teams under 30 users; enterprise license required for larger teams.
Released: July 2025
Category: AI agent tool
Website: archestra.ai

Key features

Model Context Protocol registry and gateway
LLM proxy with spend limits and routing
Identity integration with Okta and Entra ID
Policy enforcement before tool execution
Telemetry export via OpenTelemetry and Prometheus
Managed and sandboxed AI agent runtime
Budget tracking per person, team, or agent

Use it for

Manage and secure internal AI agents
Control access to company data and tools
Route model traffic and manage spend limits
Audit AI actions and trace user identities

Alternatives to Archestra

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Astrid — It replaces prompt-based trust with OS-grade, capability-based security.
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