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.

Learn more โ†’

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.

Learn more โ†’

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.

Learn more โ†’

Agent Collaboration (A2A)

Agents within your formation work together seamlessly. Delegate tasks across formations. Collaborate with external agents from other organizations via A2A protocol.

Learn more โ†’

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.

Learn more โ†’

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%+.

Learn more โ†’

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.

Learn more โ†’

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.

Learn more โ†’

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.

Next Steps