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MnemeHQ/mneme

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Open-source architectural drift prevention for the agentic AI SDLC. Deterministic guardrails keep AI coding agents aligned with repository architecture.

MCP

MnemeHQ/mneme

Added 23 Sept 2026

#adr #agentic-ai #agentic-ai-sdlc #ai-agent #ai-agents #ai-coding #anthropic #architectural-decision-records

Overview

Open-source architectural drift prevention for the agentic AI SDLC. It applies deterministic guardrails to keep AI coding agents aligned with repository architecture. Written in Python, it is designed to enforce structural rules during AI-assisted development.

Best for

Best for
Teams using AI coding agents that need automated architectural enforcement

Use cases

  • Prevent AI agents from introducing architectural violations
  • Enforce repository structure in CI/CD pipelines
  • Maintain consistent architecture when using multiple coding agents

How to use

Install

pip install mneme-hq

Tested with

Claude Code, Cursor

Notes

Open-source architectural drift prevention for the agentic AI SDLC. It applies deterministic guardrails to keep AI coding agents aligned with repository architecture. Written in Python, it is designed to enforce structural rules during AI-assisted development.

21 stars on GitHub. Last updated 2026-09-23. Licensed MIT.

Use cases

  • Prevent AI agents from introducing architectural violations
  • Enforce repository structure in CI/CD pipelines
  • Maintain consistent architecture when using multiple coding agents

Pros

  • Deterministic guardrails, not probabilistic
  • Open-source and Python-based
  • Targets a real pain point in AI-driven development

Cons

  • Very early stage with only 21 GitHub stars
  • Limited community and ecosystem
  • Requires manual setup and rule definition

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

Pros

  • Deterministic guardrails, not probabilistic
  • Open-source and Python-based
  • Targets a real pain point in AI-driven development

Cons

  • Very early stage with only 21 GitHub stars
  • Limited community and ecosystem
  • Requires manual setup and rule definition
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