AIエージェント
mcp-gateway-registry
An enterprise MCP gateway: governed, auditable tool access for agents.
★ 964 スターApache-2.0
ガイドを見る →archestraは、archestra-aiが公開しているオープンソースのAIエージェントプロジェクトです（GitHub: archestra-ai/archestra）。GitHubスターは4,355、フォークは1,212で、NOASSERTIONライセンスの下で公開されています。GitHubでの最終更新は2026年10月8日です。
Archestra: the enterprise AI platform — chat UI, LLM gateway, and MCP gateway with guardrails
Decide between the one-command Docker quickstart for evaluation and Helm/Kubernetes for production.
Pull and start the Archestra platform container, mounting the Docker socket and data volumes as documented.
Add your LLM providers, configure OIDC/SAML SSO and roles, and set cost limits.
Give teams the internal chat UI, then register MCP servers behind the gateway with your guardrail rules.
A ChatGPT-style interface for employees that works with many models, tools, and knowledge bases.
One endpoint for Anthropic, OpenAI, Azure, Bedrock, DeepSeek, and more, with dynamic routing and virtual API keys carrying cost limits.
OAuth and on-behalf-of flows for users, a private MCP registry, isolated per-server deployments, and an MCP orchestrator with a Kubernetes operator.
Scheduled, email, webhook, A2A, chat, and API-triggered agents with skills, sub-agent delegation, and sandboxed code execution.
Deterministic tool-call rules, Dual-LLM verification for sensitive calls, and Lethal Trifecta protections.
OIDC/SAML SSO (Okta, Entra ID), RBAC with custom roles, OpenTelemetry traces, Prometheus metrics, and per-team cost tracking.
Clone the project and enter its directory (for source work or Helm charts).
git clone https://github.com/archestra-ai/archestra.git
cd archestraStart the platform with quickstart mode enabled and persistent volumes.
docker pull archestra/platform:latest
docker run -p 127.0.0.1:9000:9000 -p 127.0.0.1:3000:3000 -e ARCHESTRA_QUICKSTART=true -v /var/run/docker.sock:/var/run/docker.sock -v archestra-postgres-data:/var/lib/postgresql/data -v archestra-app-data:/app/data archestra/platform:latestVisit the local UI and finish setup (providers, SSO) from the admin screens.
# open http://127.0.0.1:3000 after the container startsarchestra-ai, the company behind the Archestra platform (Archestra.AI).
It is an open-core platform: per the README, it is free for teams under 30 users, with enterprise licensing beyond that; the license field in the repo metadata is unasserted (NOASSERTION).
You connect your own LLM provider accounts (Anthropic, OpenAI, Azure, Bedrock, etc.) to the gateway.
LiteLLM focuses on the LLM gateway layer; Archestra bundles the gateway with an employee chat UI, an MCP gateway/registry, an agent runtime, guardrails, and SSO/RBAC as one platform.
Run the documented `docker run` quickstart command, open the local UI, and connect your first LLM provider.
An enterprise MCP gateway: governed, auditable tool access for agents.
Enterprise LLM app platform: GenAI workflows, RAG, agents, model management, evaluation, fine-tuning.
Programmable guardrails to keep LLM systems safe and on rails.
Unla MCP Gateway: turn existing APIs and MCP servers into MCP endpoints with zero code changes.
A blazing-fast enterprise AI gateway: 1000+ models, sub-100µs overhead.
MCP aggregator, orchestrator, middleware and gateway in one Docker — compose many servers into one endpoint
LibreAIカタログに掲載されたAIエージェントプロジェクトの中で最もスターの多いもの — archestraが合わなかった場合に検討したい、現実的な候補リストです。
A personal AI that really does things — on any OS, with your data staying yours.
An agentic skills framework & software development methodology that works.
Agent harness optimization system with skills, memory and security for Claude Code, Codex and more
The agent that grows with you — a Python framework for adaptive AI agents.
DeepSeek's plugin-based agent harness where everything is a plugin.
カタログの中でarchestraとスター数が近いAIエージェントプロジェクト — 前後の棚もそのまま見て回れます。
nono: zero-trust, zero-setup, zero-latency sandboxing and runtime security for AI agents
Monid — OpenRouter for agent tools: one base URL and one key give an agent 2,000+ tools across 72+ providers
The Ruby-native AI framework. Chats, agents, tools, images, audio, and video through one consistent API, in plain Ruby or Rails.
ArcBox: a fast macOS-native container and VM runtime — a drop-in Docker engine with agent sandboxes
Memory-LanceDB-Pro gives OpenClaw agents hybrid search, smart extraction, and intelligent forgetting
AdalFlow: The library to build & auto-optimize LLM applications.