What is MUXI?
The AI Application Server
No one builds their own Nginx to deploy a website. No one should reinvent infrastructure to build AI.
MUXI is production-ready infrastructure for AI agents. Not a framework. Not a wrapper. A server.
Think of it this way:
- Websites have web servers (Nginx, Apache)
- APIs have application servers (Express, FastAPI)
- Agents now have MUXI
flowchart TB
subgraph "The MUXI Stack"
A["<b>SDKs:</b><br>Python, TypeScript, Go, Swift, Java..."]
B["<b>APIs:</b><br>REST endpoints for chat, deploy, stream"]
C["<b>Runtime:</b><br>Agents, memory, tools, orchestration"]
D["<b>Server:</b><br>Multi-formation deployments, auth, routing"]
end
How it runs
Like a web application:
| Layer | Web World | MUXI |
|---|---|---|
| Server | Nginx | MUXI Server |
| Runtime | Node / Python | MUXI Runtime |
| Application | Your code | Formation |
How you ship it
Like Docker:
| Concept | Docker | MUXI |
|---|---|---|
| Engine | Docker Engine | Server + Runtime |
| Definition | Dockerfile | Formation |
| Registry | Docker Hub | MUXI Registry |
| CLI | docker
| muxi
|
The key insight: You build applications ON TOP of MUXI using SDKs. Your frontend, mobile app, or backend talks to MUXI via API. MUXI handles orchestration, memory, multi-tenancy, and observability.
That's what makes it infrastructure, not a framework.
The Problem
Building a demo agent is easy:
response = openai.chat("Hello, world!")
Building a production agent system requires:
- Multi-agent orchestration and coordination
- Memory management (short-term, long-term, semantic)
- Tool integration (APIs, databases, file systems)
- Multi-tenant isolation and security
- Observability and debugging
- Deployment, scaling, and lifecycle management
Most teams spend 3-6 months building this infrastructure before shipping a single feature.
The question: Is agent infrastructure your core IP, or is it plumbing blocking your actual product?
The Solution
MUXI treats agents as native infrastructure primitives. Declare them in YAML, deploy with one command, manage like containers.
Declare your system in YAML
# formation.afs - A complete AI system definition
schema: "1.0.0"
id: customer-support
llm:
models:
- text: openai/gpt-4o
agents:
- id: triage
role: "Route customer inquiries"
- id: technical
role: "Handle technical issues"
- id: billing
role: "Handle billing questions"
memory:
persistent:
enabled: true
mcp:
servers:
- id: zendesk
- id: stripe
Deploy with one command
muxi deploy
# That's it. You're live.
Build on top
from muxi import MuxiClient
client = MuxiClient("http://server:7890/api")
response = client.chat("customer-support", "I need a refund", user_id="user_123")
Key Capabilities
LLM-Agnostic
Use OpenAI, Anthropic, Google, Azure, AWS Bedrock, or local models (Ollama, llama.cpp). Swap providers in seconds. Mix models per agent. Automatic failover when providers fail.
Multi-Tenant by Design
Each user stores their own credentials โ OAuth tokens, API keys, connection strings. Complete session isolation. One formation serves thousands of users with personalized experiences.
Intelligent Orchestration
The Overlord automatically breaks down complex requests into subtasks. No predefined workflows โ agents analyze complexity, identify dependencies, and execute in optimal order.
Agent Collaboration (A2A)
Agents within your formation work together seamlessly. Delegate tasks across formations. Collaborate with external agents from other organizations via A2A protocol.
1,000+ MCP Tools
Access GitHub, Slack, Stripe, databases, file systems, and more through Model Context Protocol. Unlike typical implementations, MUXI indexes tool schemas once โ not dumped into every context window.
Three-Tier Memory
Buffer memory for immediate context. Persistent memory across sessions. Vector memory for semantic retrieval. User synopsis caching reduces token usage by 80%+.
Knowledge & RAG
Pre-load agents with domain knowledge from files and URLs. PDFs, markdown, Office docs, images โ agents retrieve relevant context without fine-tuning. Update knowledge by updating files.
Real-Time Streaming
Stream responses as agents think, not after completion. SSE and WebSocket support. Token-by-token delivery for chat interfaces. Progress updates for multi-step operations.
Built for Efficiency
MUXI isn't a prototype tool โ it's production infrastructure with the numbers to prove it.
| Metric | Value |
|---|---|
| Time to first agent | 5 Minutes |
| Response time | <100ms time to first token |
| Test coverage | 80%+ test coverage across core components |
| Observability Events | 349 typed events |
| LLM supported | 21+ providers, 300+ models |
| LLM cost saving | 50-80% via semantic caching |
Declare Once, Deploy Everywhere
MUXI created the Agent Formation Schema โ an open spec for declarative AI systems. Agents, knowledge, tools, and settings defined in portable .afs files.
Like a Dockerfile for containers, but for agents.
Formations are:
- Portable โ Run anywhere MUXI runs
- Versionable โ Git-friendly YAML files
- Shareable โ Push to the registry, pull anywhere
The Formation Registry
Discover and share formations through the MUXI Registry. Like Docker Hub, but for AI agents.
# Pull a pre-built formation
muxi pull @acme/customer-support
# Publish your own
muxi publish my-agent:1.0.0
Browse community formations, install with one command, customize for your needs.
Open Source & Self-Hosted
MUXI is open-source and self-hostable. Your data stays on your infrastructure. No vendor lock-in. No per-seat pricing. No usage limits. Free forever. Revenue from optional support services.
- Full source code on GitHub
- Single binary installation
- Works on Linux, macOS, Windows, Docker
- Enterprise features available
How It Compares
MUXI makes frameworks obsolete for 90% of use cases.
| MUXI | Frameworks (LangChain, CrewAI) | Cloud AI (Bedrock, Vertex) | |
|---|---|---|---|
| What it is | Infrastructure | Library | Managed service |
| Deployment | muxi deploy
| You build it | Vendor-managed |
| Multi-tenancy | Built-in | You build it | Limited |
| Self-hosted | Yes | N/A | No |
| LLM choice | Any provider | Any provider | Vendor models |
| Observability | 349 events | You build it | Vendor tools |
vs. AI Assistants (OpenClaw, ChatGPT)
Different layer entirely. OpenClaw is a personal AI assistant (single-user product). MUXI is infrastructure to build products like OpenClaw โ with multi-tenancy, proper memory, and SDKs for integration.
MUXI is infrastructure, not a framework. Frameworks help you write agent logic. MUXI runs agents in production.
Who Is MUXI For?
Platform Builders
Building a SaaS with AI features? MUXI handles orchestration, memory, and multi-tenancy so you can focus on your product.
Internal Tool Builders
Deploying AI assistants for your team? MUXI gives you SOPs, observability, and enterprise-grade infrastructure out of the box.
Developers Tired of Framework Hell
Spent months on LangChain orchestration code? MUXI replaces it with YAML configuration and a single deploy command.