Built to democratize AI. Powered by .NET.
OpenMono is a coding agent that runs entirely on your hardware — no subscriptions, no data leaving your network, no per-token billing. It pairs a .NET 10 CLI with its own llama.cpp inference server, giving you a full agentic loop with 20 built-in tools, Docker sandboxing, and deep code intelligence. NVIDIA GPU, CPU, or Apple Silicon (Metal) — it auto-configures itself. You own the model, the compute, and the data.
One command. Auto-detects GPU · CPU · Apple Silicon. Installs model, runtime, and Docker containers.
bash <(curl -fsSL https://raw.githubusercontent.com/StartupHakk/OpenMonoAgent.ai/refs/heads/main/get-openmono.sh)Then from any project:
openmono agent # TUI mode (default)
openmono agent --classic # classic scrolling terminal→ Full command reference — daily commands, setup flags, GPU/CPU options
Get them: openmono setup search · OPENMONO_VISION_ENABLED=1 · App Store · Google Play · VS Code Marketplace
Most coding agents are cloud products wearing an open-source label. Your prompts, your code, and your context hit someone else's servers on every keystroke. OpenMono runs the model on your hardware — after the one-time setup, inference costs nothing. Your code never leaves the machine. No account. No usage dashboard. No API key.
→ Full architecture + diagram · 4 providers · runs at ~45 tok/s on GPU, ~20 tok/s on CPU
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01 · Bundled inference — zero config, zero cost
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02 · Agentic loop that earns its name |
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03 · 20 tools, 12-step pipeline |
04 · 5 specialist sub-agents
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05 · Docker sandbox |
06 · Deep code intelligence Auto-detects graphify (semantic concept graph, 25+ languages) and code-review-graph (structural call graph via MCP, ~22 tools) if installed — no config needed. |
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07 · Playbooks |
08 · 4 providers, hot-swappable |
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09 · Distributed inference |
10 · Vision |
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11 · Private web search & scraping
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12 · VS Code extension
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Auto-detects GPU · CPU · no config needed. On Linux, 12 GB and 16 GB cards run lower-accuracy models; use a 24 GB card for best results. Requires Ubuntu 26.04 LTS (recommended) or 25.10. On macOS, the full and inference roles require Apple Silicon (M1+); 64 GB+ unified memory is the recommended, tested configuration. Less than 64 GB is not encouraged — smaller model, much tighter context window. Intel Macs: agent-only mode. macOS 14+ (Sonoma/Sequoia) recommended.
Roadmap |
What's next |
Setup & commands |
Daily commands, TUI vs classic, flags |
Architecture |
.NET CLI + llama.cpp + Docker, full diagram |
Models & reasoning |
Model tiers, reasoning mode, provider config |
Configuration |
settings.json, providers, permissions, MCP servers |
Playbooks |
YAML workflows, typed params, checkpoint/resume |
graphify |
Semantic code graph, 25+ languages |
code-review-graph |
Structural call graph via MCP |
VS Code extension |
Chat panel for VS Code 1.85+ · also works in Cursor · Marketplace |
Contributing |
How to contribute |
| PUBLIC BETA Early access is open — we're shipping updates fast. Try it out and tell us what you'd like to see next. |
| OpenMono is early and moving fast. Contributions are welcome — new tools, providers, LSP servers, playbooks, bug fixes, or docs. |
→ Read the contributing guide before opening a PR
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"AI shouldn't be a subscription you rent. It should be infrastructure you own —
sitting on your desk, serving your code, answering only to you."
— Startup Hakk
GNU AFFERO GENERAL PUBLIC LICENSE v3.0 · © 2026 StartupHakk
