Local Multi-Agent AI Setup on WSL Using OpenClaw and Ollama
Architecture Overview
A developer has documented their local multi-agent AI setup running entirely on WSL Ubuntu 24.04 on Windows. The system uses OpenClaw 2026.2.26 as an open-source gateway that connects AI agents to messaging apps like Telegram, creating private AI infrastructure under full user control.
Agent Configuration
The setup consists of four specialized agents:
- Pluto - The coordinator that routes tasks to appropriate agents. Runs on OpenRouter (free tier).
- Hermes - Handles research, writing, web browsing, content tasks, and API integrations like YouTube. Uses OpenRouter.
- Vulcan - Coding and automation agent running 100% locally on Ollama with qwen2.5-coder model, resulting in zero API costs.
- Aegis - Security monitoring and read-only system auditing. Uses OpenRouter.
Technical Implementation Details
The stack includes:
- OpenClaw 2026.2.26
- Ollama with models: qwen2.5-coder, codellama, llama3.2
- OpenRouter API
- Telegram bots (one per agent)
- WSL Ubuntu 24.04
- systemd for process management
Cost and Configuration
Total spend is less than $0.01, with Vulcan being completely free (local Ollama). The other three agents use OpenRouter's auto-routing feature that selects the most cost-effective models. The developer set a $5/month hard cap on OpenRouter as a safety net.
Key Learnings
- WSL + systemd works effectively for running the gateway as a background service that survives reboots
- Ollama model auto-discovery in WSL has quirks - manual registration of provider config was required
- Delegation between agents works well once the coordinator's instructions are properly tuned
- The Chrome browser relay for live web access requires port 18792, not the gateway port (caused an hour of troubleshooting)
📖 Read the full source: r/openclaw
👀 See Also
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