CLRK, an open-source agent runtime with gVisor and MitM guardrails
TL;DR: we built a framework-agnostic agent runtime that uses gVisor for isolation and runs on k8s. It’s open-source under AGPLv3 Recently we’ve been working on a customer support “AI assistant” - essentially an interactive knowledge base/L1 support but with an option to touch resources that belong to a customer it’s talking to. We found existing tools to be lacking in these aspects: 1. Fully intercepted i/o. We wanted to trace out LLM calls as well as any other networking calls attempted by the harness so that guardrails and audit trails apply to all current and future systems…
CLRK, an open-source agent runtime with gVisor and MitM guardrails launched on July 7, 2026 with 5 votes, #4,557 of 24,623 launches that month and more than 75% of that year's launches.
What it does
Cognitive Loop Runtime for Kubernetes. Contribute to apoxy-dev/clrk development by creating an account on GitHub.
CLRK (we pronounce it as "clerk") is a Kubernetes-native runtime for LLM agents. It runs each agent in a gVisor sandbox and transparently intercepts all egress - LLM APIs, MCP, tool calls - without modifying agent code. That interception point gives you observability, policy enforcement, and routing-based cost control over agents you don't otherwise get to see inside. CLRK runs untrusted, framework-agnostic agent workloads in gVisor sandboxes. You describe an agent declaratively - a container image + a trigger + an egress policy - and CLRK schedules it onto a pool of sandbox workers. It brings its own scheduler, so agent startup isn't gated on pod-creation latency. Every byte in or out of…from github.com
In the maker’s words, at launch
TL;DR: we built a framework-agnostic agent runtime that uses gVisor for isolation and runs on k8s. It’s open-source under AGPLv3 Recently we’ve been working on a customer support “AI assistant” - essentially an interactive knowledge base/L1 support but with an option to touch resources that belong to a customer…
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