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omega-memory/omega-memory

v1.4.9 Feature

This release adds 1 notable feature for engineering teams evaluating rollout.

Published 1mo MCP Developer Tools
✓ No known CVEs patched
Read the diff → Tool health → What is this tool? →

✓ No known CVEs patched in this version

Topics

ai-agent ai-memory claude claude-code coding-agent context-engineering
+11 more
cursor knowledge-graph llm local-first mcp mcp-server memory model-context-protocol persistent-memory semantic-search windsurf

Summary

AI summary

Reranker precision selection allows using an int8 quantized model (~571 MB) instead of the FP32 default.

Full changelog

Features

  • Reranker precision selection -- Set OMEGA_RERANKER_PRECISION=int8 to use the quantized model (~571 MB on disk, ~650 MB RSS) instead of the FP32 default (~2.3 GB on disk, ~2.5 GB RSS). Also available via download_model(precision="int8"). Auto-detect finds whichever variant is installed.

Upgrade

pip install --upgrade omega-memory
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About omega-memory/omega-memory

Persistent memory for AI coding agents with semantic search, auto-capture, cross-session learning, and intelligent forgetting. 12 MCP tools, local-first.

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Related context

Beta — feedback welcome: [email protected]