HELM is a tool designed to block unsafe actions by AI agents before they are executed. It operates locally, providing a mechanism for approvals, denials, and escalations of AI-agent requests. The system records receipts for actions, allowing for offline verification of local evidence. Users can run a local approval loop to protect coding agents, and the tool can be added to specific coding agents such as Codex or Claude Code.
HELM offers integration with OpenAI-style clients through a proxy, enabling clients to point at HELM for request handling. It provides both a command-line interface and an HTTP API for interacting with its features. Users can write policies to govern AI-agent actions, and the system responds to requests with outcomes such as ALLOW, DENY, or ESCALATE, with receipts written for blocked actions.
Installation instructions reference using Homebrew to install the helm-ai-kernel, and there are guides and references available for setup, integrations, and troubleshooting. The documentation emphasizes local deployment and offline verification, supporting use cases where AI safety and policy enforcement are priorities.
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HELM Docs is a LLM eval & observability product. It focuses on preventing unsafe or unauthorized actions by AI agents through local policy enforcement and approvals. It is built as an open-source project for developers and organizations deploying AI agents. HELM Docs is open source under the Apache-2.0 license. It runs on the web and the command line, and it can be self-hosted.
Mindburn Labs builds and maintains HELM Docs, and the product first shipped in 2026. Development happens publicly on GitHub with 69 stars and 479 commits in the last 90 days. PulseGate's similarity index finds few close equivalents — HELM Docs occupies a relatively distinct niche. Key capabilities include policy enforcement, local approvals, and audit receipts. It exposes integrations via a public API and an MCP server.
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Mindburn-Labs/helm-ai-kernel discovered by the PulseGate indexer
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