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metabolism-tools/workspace-metabolism

by Various

Govern what Claude Code, Codex, Aider and OpenClaw leave in your workspace: one JSON policy file, audit, recyclable clean, rollback, hash-chained audit trail.

MCP

metabolism-tools/workspace-metabolism

Added 21 Sept 2026

#ai-agents #ai-governance #audit #claude-code #cleanup #cli #developer-tools #dsh-plugin

Overview

Workspace governance tool for AI coding agents. Uses a single JSON policy file to control, audit, and clean files left by Claude Code, Codex, Aider, and OpenClaw. Provides rollback and a hash-chained audit trail.

Best for

Best for
Developers using multiple AI coding agents who want centralized workspace cleanup and audit.

Use cases

  • Enforce cleanup policies for agent-generated files
  • Audit workspace changes with a hash-chained trail
  • Roll back unwanted files left by coding agents

How to use

Install

pip install workspace-metabolism

Tools exposed

  • retention_days
  • remote_authoritative
  • review_after

Tested with

Claude Code, Cursor

Notes

Workspace governance tool for AI coding agents. Uses a single JSON policy file to control, audit, and clean files left by Claude Code, Codex, Aider, and OpenClaw. Provides rollback and a hash-chained audit trail.

2 stars on GitHub. Last updated 2026-09-21. Licensed MIT.

Use cases

  • Enforce cleanup policies for agent-generated files
  • Audit workspace changes with a hash-chained trail
  • Roll back unwanted files left by coding agents

Pros

  • Single JSON policy file covers multiple agents
  • Includes audit and rollback capabilities
  • Simple Python-based tooling

Cons

  • Very low GitHub star count (2) suggests limited community traction
  • Only supports the four listed agents
  • Requires Python setup and manual policy configuration

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Single JSON policy file covers multiple agents
  • Includes audit and rollback capabilities
  • Simple Python-based tooling

Cons

  • Very low GitHub star count (2) suggests limited community traction
  • Only supports the four listed agents
  • Requires Python setup and manual policy configuration
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