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bernstein

The open‑source AI Agents Governance & Orchestration framework: write the rules declaratively, Bernstein enforces them and produces the verifiable, replayable record. Free, Apache-2.0. https://bernstein.run

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ai-governancedockerai-agentstamper-evidentaudit-logagent-orchestratordeterministic-replayair-gapPythonllm-orchestrationaudit-trailagent-fleetprovenancecomplianceparallel-agentsagent-governanceorchestratorreproducibilitypythongit-worktreemcp-serveragent-infrastructureai-orchestrationpython/uv

Bernstein is an open-source AI agent governance and orchestration framework that you configure by writing rules declaratively; it enforces those rules and produces a verifiable, replayable record of agent activity. It ships as an MCP server with a Python toolchain (Docker, uv) and includes config artifacts such as agents.md, claude.md, cursor rules, devcontainer, and MCP config/manifest.

Reach for it when you need declarative rule enforcement over AI agents with a tamper-evident, auditable trail for compliance or reproducibility.

Use it to

  • Enforce declarative governance rules on agent fleets
  • Produce tamper-evident audit logs and attestations
  • Run deterministic replay of agent sessions
  • Orchestrate parallel agents using git worktrees
  • Operate agents in air-gapped environments

For Teams running AI agents under compliance or audit requirements

Role
mcp-server
Language
Python
Licence
Apache-2.0
Forks
161
Open issues
251
Last push
2026-09-17
Latest release
v1.0.0 · 2026-03-29
topicsagent-governanceorchestrationaudit-traildeterministic-replaymcp-servercompliance