Running Local LLM Agents on Mac Minis with Telegram Interface

A developer on r/LocalLLaMA detailed a system for running multiple local LLM agents on Mac Minis, controlled entirely through Telegram messages from a phone. The setup eliminates API costs and provides complete privacy while maintaining functionality similar to commercial services like Claude Code Channels.

Technical Setup

The core system uses:

• Local models through LMStudio: 35B models for everyday tasks, 235B models for heavier reasoning
• Claude Code running in tmux sessions on each Mac Mini
• Telegram bots that bridge user messages to the tmux sessions
• 80 lines of Python for the Telegram bot implementation (available on GitHub)

The workflow is straightforward: text a message to the Telegram bot, which types it into the tmux session, watches for output, and sends the response back.

Key Advantages

• Zero ongoing cost: Hardware is the only expense—no API keys, rate limits, or quota restrictions
• Complete privacy: Everything stays on the local area network (LAN)
• Model flexibility: Mix and match different models—one agent runs Gemini CLI, others use LMStudio pointed at Ollama models
• No vendor lock-in: LMStudio serves the Anthropic Messages API natively, so Claude Code connects to it as if talking to Anthropic's servers

Current Implementation

The developer runs 5 specialized agents, each with its own Telegram bot:

• Approval workflows with inline Telegram buttons (Approve/Reject/Tweak) for reviewing drafts from a phone
• Shared memory across agents via git synchronization
• Media generation (FLUX.1, Wan 2.2) dispatched to a GPU box
• Podcast pipeline with cloned voice TTS, triggered from a single Telegram message

Hardware Requirements

• 35B models: Run well on 64GB+ RAM Mac or 24GB GPU
• 235B models: Need 128-256GB RAM or multiple GPUs
• The developer recommends starting small and scaling as needed

The tmux bridge pattern is model-agnostic—it doesn't care what's running inside the session, allowing for easy swapping of underlying models. A full build guide for a single machine/agent is available, with multi-machine instructions coming soon.