runiq

I love local LLMs, but I hate that they are trapped in a text box. I wanted my AI to actually use my computer—open the browser, find a file, organize a folder—just like a human would. Existing tools were mostly fragile Python wrappers or required giving the agent "god mode" (root) which terrified me. So I built Runiq. It’s a single static Go binary that implements the Model Context Protocol (MCP). It gives Claude/Llama access to your File System and Browser, but acts as an "OS Firewall." It intercepts every dangerous syscall (like write or delete) and forces a native popup for your approval. Why Go? Single Binary: No pip install dependency hell. Concurrency: Handles the MCP stream + user input + file I/O without lag. Safety: Stricter permission structs than Python. It’s open source. I’d love to hear how you guys are handling agent permiss

Hi HN — I built Runiq: a local “sovereign runtime” that lets LLM agents (Claude Desktop, local Llama, etc.) use hardened tools to interact with your OS, instead of executing arbitrary shell/Python. Runiq implements Anthropic’s Model Context Protocol (MCP) and exposes a small set of controlled capabilities: Stealth Chromium browser for scraping/automation (aimed to survive common bot checks) File operations and local workflow tools Human-in-the-loop security: native OS popups block risky actions (write/delete/etc.) until you approve It ships as a single static Go binary (no venv/daemon). It’s localhost-only and auditable; if you pair it with a local model, nothing leaves your machine. There’s also an optional Python adapter to use the same tool interface with OpenAI/Groq/LangChain-style agents. Repo: https://github.com/qaysSE/runiq I’d lov