Enkstein puts a policy layer between you and every AI coding agent you run — Codex, Claude, Gemini, browser companions, API calls, and local Ollama models — from a single self-hosted desktop workspace.
The MIT-licensed tool, posted to r/LLMDevs, gives you:
- Policy-aware routing — sensitive work stays local on Ollama instead of hitting cloud APIs
- Project-scoped file access — agents can only touch files inside an approved folder
- Approval gates — consequential actions require explicit sign-off before execution
- Audit trail — logs the model used, policy outcome, redactions applied, and files changed
- Security missions — connector-based assessments and governed remediation workflows
The core pitch is control. Most AI coding tools assume you trust the model with your codebase and your data. Enkstein sits in front of them and enforces boundaries — routing restricted work to local models, scoping file writes, and recording what each agent actually did.
NOTE
Docker Desktop is currently required for the local runtime. The project is MIT-licensed but still an early preview — expect rough edges.
This fits a broader shift. Developers running local models through Ollama alongside cloud agents now have multiple paths — OpenCode for free local inference, open-agent-sdk for extracted agent internals. Enkstein’s angle is the governance layer — not replacing your agents, but constraining them.
Available now on GitHub under MIT license. If you’re routing sensitive code through multiple AI agents and want a single audit trail, this is worth a look — but verify Docker Desktop compatibility before deploying.