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Causal-Memory-Layer MCP Server

safal207/Causal-Memory-Layer

Score: 47.9 Rank #19007 MCP Server
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CML (Causal Memory Layer) — a foundational memory layer for recording reasons, permissions, and responsibility behind actions, not just events or results. Enables systems in AI, fintech, security, and distributed computing to preserve meaning and causal accountability across time, independent of execution or transport.

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Overview

safal207/Causal-Memory-Layer is a Python tool licensed under MIT. CML (Causal Memory Layer) — a foundational memory layer for recording reasons, permissions, and responsibility behind actions, not just events or results. Enables systems in AI, fintech, security, and distributed computing to preserve meaning and causal accountability across time, independent of execution or transport.

Ranked #19007 out of 24840 indexed tools.

Actively maintained with commits in the last week.

Ecosystem

Python MIT

Score Breakdown

StarsFreshnessIssue HealthContributorsDependents
Stars 15% 4

4 stars → early stage

Freshness 25% 1d ago

Last commit 1d ago → actively maintained

Issue Health 25% 0%

0/84 issues closed → many open issues

Contributors 10% 0

0 contributors → solo project

Dependents 25% 0

No dependents → no downstream usage

npm Downloads N/A
PyPI Downloads N/A
Forks 6
Description Detailed
License MIT

Weights: Freshness 20% · Issue Health 20% · Dependents 22% · Stars 10% · Contributors 8% · How we score →

How to Improve

Issue Health high impact

You have 84 open vs 0 closed issues — triaging stale issues improves health

Contributors medium impact

Single-contributor projects carry bus-factor risk — welcoming contributors boosts confidence

Dependents medium impact

No downstream dependents detected yet — adoption by other projects is the strongest trust signal

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