Mmcp.market

Head to head

rag-rat vs AI Model Lifecycle Index

Same numbers we show everywhere else, lined up. Ratings come from users, the grade comes from our scanner, adoption comes from public registries.

rag-ratio.github.cq27-dev/rag-rat
B
No reviews yet

Repository intelligence, code graph, history, papertrail, and cross-agent memory for coding agents.

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AI Model Lifecycle Indexio.github.oscarlopez-gif/ai-model-lifecycle-index
A
No reviews yet

Cross-vendor AI model lifecycle: status, sunset dates, and migration targets, source-cited.

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The short version

Neither has been reviewed yet, so the comparison rests on the scan and the public usage numbers. The safety scan favours AI Model Lifecycle Index (88/100 against 75). AI Model Lifecycle Index is hosted and callable through the gateway; rag-rat runs on your own machine. rag-rat has noticeably more public adoption.

 rag-ratAI Model Lifecycle Index
User ratingNo reviews yetNo reviews yet
Safety gradeB75/100A88/100
AdoptionGrowingGrowing
GitHub stars200
Downloads / week330–
Runs whereYour machine (local)Hosted (remote)
Gateway-readyNoYes
Tools—4
Write actions——
Price per callFreeFree
LicenceMITNOASSERTION
Last release2026-09-192026-09-19
CategoryAI and agentsAI and agents

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