SRR—a local-first Linux agent toolkit harness. By pairing custom systemd configurations with an independent MCP server and a SearXNG web proxy, SRR can scale from small 4B models all the way up to 70B local LLMs with limitless token usage and native web retrieval capabilities. It also has a full harness with a multitude of capabilities.
How do you build a local AI agent harness that searches the internet with zero API bills or token restrictions? You bypass third-party providers completely.
I take you under the hood of my home lab running on an older ThinkPad P70. After getting frustrated with bugs and limitations in early setups of OpenClaw and Hermes, I built SRR—a local-first Linux agent harness.
By pairing custom systemd configurations with an independent MCP server and a SearXNG web proxy, SRR can scale from small 4B models all the way up to 70B local LLMs with limitless token usage and native web retrieval capabilities.
It is a Swiss Army Knife Ai system on Linux that's able to build and use its own tools. Work is always in progress. And live demos will be posted on @thesp_cemanchannel for future testing and capabilities.