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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.

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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.

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Core Features

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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

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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

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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
)

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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

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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"}
  }'

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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

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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

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Next Steps