What is Laddr?

Laddr is an open-source multi-agent framework that helps developers build, orchestrate, and scale intelligent multi-agent systems with ease. AI teams and developers around the world use Laddr to manage distributed agent systems, trace execution, and scale parallel tasks effortlessly.

Why Laddr?

Building production-ready multi-agent systems is complex. You need:

Orchestration - Coordinate multiple agents working together
Scalability - Handle high throughput with parallel workers
Observability - Track execution, debug issues, monitor performance
Flexibility - Connect your own tools, APIs, and models
Reliability - Handle failures, retries, and error recovery

Laddr provides all of this out of the box.

Core Features

Scalability

Queue-based architecture with parallel agent workers. Scale horizontally by adding more workers, or vertically by increasing worker capacity.

# Scale workers dynamically
laddr scale researcher 5
laddr scale coordinator 3

Observability

Docker-based dashboard with real-time traces, token usage, and system metrics. Track every agent execution, tool call, and LLM interaction.

# Access dashboard
laddr run dev
# Open http://localhost:5173

Extensibility

Connect your own tools, APIs, and external models with full control. Use MCP (Model Context Protocol), custom tools, or system tool overrides.

from laddr import Agent
from laddr.core.mcp_tools import MCPToolProvider

mcp = MCPToolProvider(
    command="npx -y @modelcontextprotocol/server-filesystem /path",
    transport="stdio"
)

agent = Agent(
    name="filesystem_agent",
    tools=[mcp],
    # ... config
)

Configurability

Flexible PostgreSQL and MinIO/S3 storage options. Choose your queue backend (Redis, Kafka, or in-memory), LLM provider, and storage backend.

# .env
QUEUE_BACKEND=redis
DB_BACKEND=postgresql
STORAGE_BACKEND=minio
LLM_PROVIDER=openai

APIs

Exposed REST endpoints for jobs, traces, prompts, and system health. Integrate Laddr into your existing infrastructure.

# Submit a job
curl -X POST http://localhost:8000/api/prompts \
  -H "Content-Type: application/json" \
  -d '{
    "prompt_name": "researcher",
    "inputs": {"query": "Latest AI trends"}
  }'

Architecture Overview

Laddr follows a distributed architecture pattern: Components:

API Server - REST API for submitting jobs and queries
Message Queue - Task distribution (Redis, Kafka, or in-memory)
Agent Workers - Execute agent tasks in parallel
Database - Store traces, jobs, and metadata
Storage - Store large artifacts and data
Dashboard - Web UI for monitoring and debugging

Quick Start

Get started with Laddr in under 60 seconds:

Quickstart Guide

Run your first agent in 60 seconds

Installation

Set up Laddr on your machine

Key Features

Explore Laddr’s capabilities

API Reference

Integrate with REST API

Next Steps

Quickstart Guide - Run your first agent
Installation - Set up Laddr
Key Features - Learn what Laddr can do
First Agent - Build your first agent

Introduction

Getting Started

Guides

Reference

Examples

Community

Why Laddr?

Core Features

Scalability

Observability

Extensibility

Configurability

APIs

Architecture Overview

Quick Start

Quickstart Guide

Installation

Key Features

API Reference

Next Steps

​Why Laddr?

​Core Features

​Scalability

​Observability

​Extensibility

​Configurability

​APIs

​Architecture Overview

​Quick Start

Quickstart Guide

Installation

Key Features

API Reference

​Next Steps

Why Laddr?

Core Features

Scalability

Observability

Extensibility

Configurability

APIs

Architecture Overview

Quick Start

Next Steps