No one builds their own Nginx to deploy a website. No one should reinvent infrastructure to build AI.
MUXI (/ΛmΚk.siΛ/) is the AI application server. Not a framework. Not a wrapper. A complete, self-hosted server stack where agents are native primitives and production capabilities are infrastructure, not application code.
Deploy complete agent formations with orchestration, auditable memory, group-based RBAC, tools, knowledge, proactive behavior, self-tuning, observability, and twelve SDKs already integrated.
Important
MUXI V1 is the stable 1.x generation. The Server, Runtime, CLI, Formation API, Server API, and all twelve SDKs move together with coordinated contracts for authentication, streaming, errors, idempotency, and response envelopes.
| Concept | Docker | MUXI |
|---|---|---|
| Engine | Docker Engine | Server + Runtime |
| Definition | Dockerfile | Formation |
| Registry | Docker Hub | MUXI Registry |
| CLI | docker |
muxi |
Note
MUXI introduced the Agent Formation Standard β an open specification for portable, declarative AI systems. A formation packages agents, knowledge, memory, tools, skills, workflows, triggers, policies, and operational behavior into one deployable unit.
Install:
brew install muxi-ai/tap/muxi # macOS
curl -fsSL https://muxi.org/install | sudo bash # Linux
powershell -c "irm https://muxi.org/install | iex" # WindowsRun:
muxi pull @muxi/hello-muxi # pull a formation
muxi deploy # deploy it
muxi chat hello-muxi # talk to itThree commands. Your formation is running, stateful, and accessible through REST, SSE, MCP, and twelve SDKs.
π Docs: Quickstart | Installation
from muxi import FormationClient
client = FormationClient(
server_url="http://localhost:7890",
formation_id="hello-muxi",
client_key="<your-client-key>"
)
for chunk in client.chat_stream({ "message": "Hello!" }, user_id="user_123"):
print(chunk.get("text", ""), end="")Official SDKs are available for Python, TypeScript, Go, Ruby, PHP, C#, Java, Kotlin, Swift, Dart, Rust, and C++.
π Docs: SDKs | API Reference
| MUXI | LangChain / LangGraph | CrewAI | AutoGen | |
|---|---|---|---|---|
| What it is | Server infrastructure | Python libraries | Python framework | Multi-agent framework |
| Deploy | muxi deploy |
Write your own | Write your own | Write your own |
| Configure | Declarative .afs files |
Imperative code | Imperative code | Imperative code |
| Multi-tenancy | User isolation and per-user credentials | Application-owned | Application-owned | Application-owned |
| RBAC | Groups, inheritance, agents, MCP, and tool rules | Build it yourself | Build it yourself | Build it yourself |
| Memory | Layered, scoped, event-sourced platform | Compose your own | Task-oriented memory | Bring your own |
| Proactiveness | Heartbeats, channels, active hours, soul documents | Build it yourself | Build it yourself | Build it yourself |
| Tools | MCP indexed once and selected at runtime | Schemas enter application context | Schemas enter application context | Tool registration |
| Operations | Deploy, update, rollback, stream, observe | Build and operate it | Build and operate it | Build and operate it |
MUXI is the infrastructure layer. Frameworks help write agent logic. MUXI deploys and operates complete agent systems.
- Formation self-tuning β operational evidence becomes reviewable revisions of
MUXI.md, backed by experiments and watched metrics. You decide what gets applied. Docs - Living, auditable memory β layered context plus user/group/formation scopes, immutable events, provenance, rebuilds, selective forgetting, decay, knowledge graphs, Captain's Logs, lessons, and signed on-premises distillation. Docs
- Proactive formations β heartbeats, active hours, per-user channels,
SOUL.md, notification routing, and built-in slash commands let formations initiate useful work instead of waiting for prompts. Docs - Reasoning RAG β navigate hierarchical document trees, combine tree and vector retrieval, and synchronize remote knowledge from cloud storage, HTTP, rsync, FTP, and SFTP. Docs
- Group-based RBAC β inheritance plus agent, MCP-server, and individual-tool allow/deny rules, with fail-closed external membership resolution. Docs
- Multi-tenant isolation β sessions, memory, artifacts, and encrypted credentials stay scoped to the user while one formation serves an entire product or organization. Docs
- Persistent artifact memory β generated documents, spreadsheets, presentations, charts, and code are versioned, encrypted, user-scoped, and recallable across sessions. Docs
- Production resilience β circuit breakers, fallback models, exponential backoff, graceful degradation, and idempotency keys make retries safe without duplicating work. Docs
- Built-in observability β hundreds of typed lifecycle events trace models, tools, memory, workflows, and triggers, with secret and entity-based PII redaction before export. Docs
- MCP in both directions β connect large tool catalogs without injecting every schema into every prompt, and expose any formation as an MCP server to Claude Desktop, Cursor, or another MCP client. Docs
- Coding-agent delegation β hand repository work to Claude Code, Droid, OpenCode, Pi, or a custom headless adapter in isolated asynchronous workspaces. Docs
- Zero-token job monitoring β deterministic polling tracks long-running MCP work without spending LLM tokens asking whether it finished. Docs
- Generative UI β streamed and non-streamed responses can carry typed options, action links, and MCP resources that all twelve SDKs expose idiomatically. Docs
- Triggers and outbound routing β schedules, webhooks, and external events activate formations, then transformers deliver results to Slack, Telegram, Discord, email, or custom destinations. Docs
- Intelligent orchestration β the Overlord routes requests, matches SOPs, decomposes complex work, coordinates agents, and can replan workflows when intermediate results change the best path. Docs
- Skills and sandboxed compute β use open
SKILL.mdpackages with progressive disclosure and execute scripts in an isolated RCE sandbox with resource and timeout controls. Docs - Hierarchical model selection β choose cloud, local, or OpenAI-compatible models at the formation, agent, SOP, trigger, skill, or workflow-step level, with aliases and fallback chains. Docs
- A2A collaboration β delegate work across formations and external agent services with API-key, OAuth 2.0, HMAC, and OpenID authentication. Docs
- Multimodal by default β process images, PDFs, audio, video, Office documents, and structured data through the same formation runtime. Docs
# formation.afs -- define your AI system (it's just YAML)
schema: "1.0.0"
id: "customer-support"
description: Helps customers with product support and refunds
llm:
models:
- text: "openai/gpt-4o"
api_keys:
openai: "${{ secrets.OPENAI_API_KEY }}"
agents:
- sales-assistant# agents/sales-assistant.afs -- define an agent
schema: "1.0.0"
id: sales-assistant
name: Sales Assistant
description: Helps customers with product questions
system_message: Help customers find products and answer questions.
knowledge:
sources:
- path: knowledge/product-info.docx
- path: knowledge/shipping-rates.csvmuxi deploy # that's it -- running, stateful, API-accessibleπ Docs: Formation Schema | Examples
-
Platform builders β Building a SaaS with AI features? MUXI handles orchestration, memory, and multi-tenancy so you can focus on your product.
-
Internal tool builders β Deploying AI systems across an organization? MUXI gives you group-based RBAC, scoped memory, per-user credentials, SOPs, observability, and self-tuning out of the box.
-
Developers tired of framework hell β Spent months on LangChain orchestration code? MUXI replaces it with YAML configuration and a single deploy command.
MUXI is open-source and self-hostable. Your data stays on your infrastructure. No vendor lock-in. No per-seat pricing. No usage limits.
- Self-hostable β run anywhere, owned by you
- Access-controlled β fail-closed group RBAC down to individual tools
- Observable β see what's happening, always
- Declarative β version-controlled and reproducible
- Open β no lock-in, no surprises
| Looking for... | Go to |
|---|---|
| Getting started | Quickstart β |
| SDKs (12 languages) | SDKs β |
| How MUXI works | ARCHITECTURE.md |
| Contributing | CONTRIBUTING.md |
| All repositories | REPOSITORIES.md |
| Licensing | LICENSE.md |
| Roadmap | Roadmap β |
This repo includes an Agent Skill that gives any compatible AI agent (Claude Code, Cursor, GitHub Copilot, VS Code, etc.) deep knowledge of the MUXI platform.
See skills/ for setup instructions.
- Star this repo to follow progress
- Discussions β ask questions, share ideas, get help
- Roadmap β see what's coming
- @muxi_ai β follow for updates
- CONTRIBUTING.md β contribute code
MUXI is created by Ran Aroussi, author of Production-Grade Agentic AI (665 pages) and an open-source developer whose tools are used by millions of developers daily.
Important
MUXI is built on the principles from Production-Grade Agentic AI β a comprehensive guide to building enterprise AI agent systems in production. Download the PDF version here βΊ.
Server and Runtime are ELv2. Everything else (CLI, SDKs, formations, schemas) is Apache 2.0.
TL;DR: Use MUXI freely for your products and business. The only restriction: don't resell MUXI itself as a hosted service. See LICENSE.md for details.
GitHub β’ Twitter β’ Discussions
For AI/LLM agents: muxi.org/llms.txt