by krillclaw
The world's smallest AI agent runtime. 49KB. Written in Zig. Zero dependencies.
# Add to your Claude Code skills
git clone https://github.com/krillclaw/KrillClaw~450KB binary. 0 dependencies. 19 source files. 50+ validated device targets. Runs on a $3 microcontroller or a cloud server.
KrillClaw is an autonomous AI agent runtime written in Zig. It connects to 20+ LLM providers (Claude, OpenAI, Ollama + 17 via --base-url), executes tools, and loops until the task is done. Includes cron scheduling, persistent KV store, MCP support, 7 messaging channels, GPIO/hardware control, and BLE/Serial transports for edge devices.
┌──────────────────────────────────────────────────────┐
│ │
│ ~450 KB. Zero deps. Boots in <10ms. │
│ The entire agent runtime — LLM client, tool │
│ executor, JSON parser, SSE streaming, cron, │
│ KV store, context mgmt — in 4,576 lines of Zig. │
│ │
└──────────────────────────────────────────────────────┘
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# 1. Install Zig 0.15+ → https://ziglang.org/download/
# 2. Clone and build (takes ~1 second)
git clone https://github.com/krillclaw/KrillClaw.git
cd KrillClaw
zig build -Doptimize=ReleaseSmall
# 3. Set your API key and go
export ANTHROPIC_API_KEY=sk-ant-...
./zig-out/bin/krillclaw "create a REST API in Go with user auth"
That's it. No npm install. No pip. No Docker. Just Zig and a binary.
Every AI agent runtime is massive. Desktop coding agents ship as 50–500MB bundles with hundreds of dependencies. The actual logic — "call LLM, parse response, execute tools, repeat" — shouldn't need any of that.
KrillClaw proves it doesn't. The same agentic ...