Self-Hosted AI Agent Orchestration: Open Source Tools 2026
You spent a week getting a single Agent working—it can search for information, write code, and send emails, running pretty smoothly. Then you realize the real task was never something one Agent could handle: you need one Agent to pull data, another to analyze, a third to write the report, and a fourth to review it, before finally sending it to the user. You try manually orchestrating them, and it ends up more exhausting than doing it yourself; you try cloud solutions, but you're uneasy about handing over your data, and the API call fees cost more than your electricity bill. How do you coordinate multiple Agents running together? It's not a capability problem—it's an orchestration problem. Here are a few self-hosted open-source orchestration tools, ranging from lightweight to heavyweight—one of them is bound to work for you.
💡 What You Will Learn
You spent a week getting a single Agent working—it can search for information, write code, and send emails, running pretty smoothly. Then you realize the real task was never something one Agent could
📜 Table of Contents
GitHub n8n-io/n8n · 52K+ Stars
GitHub langgenius/dify · 55K+ Stars
GitHub microsoft/autogen · 38K+ Stars
GitHub crewAIInc/crewAI · 25K+ Stars
from crewai import Agent, Task, Crew
researcher = Agent(role='Researcher', goal='')
writer = Agent(role='Writer', goal='')
task = Task(description='AI')
crew = Crew(agents=[researcher, writer], tasks=[task])
result = crew.kickoff()
GitHub temporalio/temporal · 13K+ Stars
GitHub agno-agi/agno · 22K+ Stars
GitHub Mintplex-Labs/anything-llm · 33K+ Stars
|:----|:---------:|:--------|:--------|:--------|
→ Temporal++
→ CrewAI / AutoGenAgent+
→ Ollama / OpenAILLM
→ n8n / API
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Written by our editorial team; tools listed here are tested or verified against public sources. Links point to official sites or GitHub repos for reference only — no paid placements.
