archestra-ai/archestra
Enterprise AI Platform with guardrails, MCP registry, gateway & orchestrator observed · 2026-08-28
Health v2 · maintenance only
81/100
- Activity 99
- Release rhythm 87
- Longevity 29
Flags: no_license
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: 0
- age_days: 414
- days_rel: 8
- days_push: 7
- n_releases_24m: 268
Adoption not part of the score
4232 stars · 1182 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
Archestra is an open-source, self-hosted enterprise AI platform combining an agentic chat UI, agent runtime, LLM gateway/proxy, MCP gateway, private MCP registry, and Kubernetes-based MCP orchestrator. It ships with enterprise features like SSO/RBAC, prompt-injection-resistant guardrails, sandboxed code execution, OpenTelemetry tracing, and per-team cost tracking.
Use cases
- self-host an internal ChatGPT-like assistant for my company
- run MCP servers securely in Kubernetes with per-user identity
- put a gateway in front of OpenAI, Anthropic, and other LLM providers with cost limits
- give non-technical teams an AI chat with SSO and RBAC
- host a private MCP registry for my team's tools
- add guardrails against prompt injection to agent tool calls
- proxy Claude Code or Cursor through one enterprise endpoint
- build and schedule autonomous agents with MCP tools and triggers
When to choose
- you need a centralized, self-hosted AI platform serving both engineers and non-technical staff
- you want MCP gateway, registry, and orchestration with OAuth on-behalf-of semantics
- enterprise requirements like SSO, RBAC, audit logs, observability, and cost tracking are mandatory
- you want drop-in LLM/MCP proxies that work with LangChain, n8n, Vercel AI, or Pydantic AI
When to avoid
- you only need a lightweight LLM API client or SDK in application code
- you want a fully permissive-licensed project (it is AGPL 3.0 with enterprise licensing)
- you need a minimal single-purpose tool rather than a full multi-component platform
- you cannot run Kubernetes or containerized infrastructure for the orchestrator
Facets
application · maturity active
agent-framework mcp rag chatbot chat-interface api-gateway auth authorization monitoring tracing security self-hosted workflow-automation scheduling webhook artificial-intelligence large-language-models chatbots self-hosted developer-tools security self-hosted cloud mcp-gateway mcp-registry mcp-orchestrator llm-gateway llm-proxy a2a agent-platform enterprise-ai guardrails sso rbac opentelemetry prometheus kubernetes-operator agentic-chat agent-skills cost-tracking ai-agents retrieval-augmented-generation devops docker kubernetes web-server typescript
10 sources
- readme: https://github.com/archestra-ai/archestra · fetched 2026-08-28 · 3b5110fdb638
- homepage: https://Archestra.AI · fetched 2026-08-29 · 8d9328f5c620
- site_page: https://archestra.ai/docs · fetched 2026-08-29 · 9126aa02e787
- site_page: https://archestra.ai/about · fetched 2026-08-29 · e431efdc87b4
- site_page: https://archestra.ai/docs/platform-chat · fetched 2026-08-29 · 7a4dc364638a
- site_page: https://archestra.ai/docs/platform-sso · fetched 2026-08-29 · f5154e95e597
- site_page: https://archestra.ai/docs/platform-agent-skills · fetched 2026-08-29 · ca737118efa0
- site_page: https://archestra.ai/docs/platform-apps · fetched 2026-08-29 · ef47899feebd
- site_page: https://archestra.ai/docs/platform-projects · fetched 2026-08-29 · f5c039a82b51
- site_page: https://archestra.ai/docs/platform-access-control · fetched 2026-08-29 · d9d9a0206655
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| archestra-ai/archestra | main | 81 |
For agents
markdown · JSON · MCP: product_card(name="archestra-ai/archestra")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem