rohitg00/agentmemory
#1 Persistent memory for AI coding agents based on real-world benchmarks
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SDKs, agent skills, IDE extensions, and reference pipelines from Backblaze Labs. All open source.
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Where it stands
Rank, growth pace and release cadence relative to everything GStars tracks.
2 releases in the last 90 days, the latest 19 days ago, with 55 contributors on GitHub.
Use Cases & Benefits
- Provides persistent memory for AI coding agents by capturing, compressing, and recalling session data across multiple agent platforms.
- Delivers high retrieval accuracy and token efficiency without external dependencies, enabling seamless multi-agent memory sharing and auto-capture with zero manual effort.
- Use for enhancing AI coding assistants like Claude Code or GitHub Copilot CLI to remember past coding sessions and preferences automatically.
- Use for building multi-agent development environments where shared memory and context improve collaboration and reduce repetitive explanations.
- Use for integrating persistent memory into custom AI tools or workflows requiring efficient, real-time recall of coding history and session context.
Should you depend on it?
License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.
License
Apache 2.0
Permissive: commercial use, modification and redistribution are allowed with attribution; includes an explicit patent grant from contributors.
Community files
- README: present
- Contributing guide: present
- Code of conduct: present
Watch-outs
No watch-outs from GStars' checks.
General guidance from repository metadata, not legal advice. How we score
From the README
Persistent memory for Claude Code, GitHub Copilot CLI, Cursor, Gemini CLI, Codex CLI, Hermes, OpenClaw, pi, OpenCode, and any MCP client.
The gist extends Karpathy's LLM Wiki pattern with confidence scoring, lifecycle, knowledge graphs, and hybrid search: agentmemory is the implementation.
Fastest path if you use a coding agent: hand it this one instruction and it installs, wires, and verifies agentmemory end to end.
Retrieve and follow the instructions at: https://raw.githubusercontent.com/rohitg00/agentmemory/main/INSTALL_FOR_AGENTS.md
On Windows the fast path is WSL2. Native Windows engine setup is manual (about 10 to 20 minutes) and
agentmemory connectis currently unsupported there. See the Windows notes below for the step-by-step.Heads-up — npx caches per version. If a bare
npx @agentmemory/agentmemoryserves an older release, force the latest withnpx -y @agentmemory/agentmemory@latest, or clear the cache once withrm -rf ~/.npm/_npx(macOS/Linux; on Windows delete%LOCALAPPDATA%\npm-cache\_npx). The first npx run from v0.9.16+ prompts to install globally inline so the bareagentmemorycommand works everywhere afterwards.Already running your own
iiiengine? agentmemory pins iii-engine v0.11.2 and won't attach to a different version (the worker can't speak another engine's protocol). Stop the other engine, then runnpx -y @agentmemory/agentmemory@latest— it installs and runs the pinned v0.11.2 in~/.agentmemory/bin, leaving your owniiiuntouched.
Daily snapshots
Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots
+3,567 stars over 86 days across 18 snapshot days; best day +109 on Aug 27.
Forks
2.6K+417
Open issues
565+135
Compared with peers in AI
Fastest-growing repositories GStars tracks in this cohort for the week of Nov 1, by 7-day star growth
| Repository | Stars | +7d | Health | Last release |
|---|---|---|---|---|
| thedotmack/claude-mem | 113.6K | +8.8K | 35 | today |
| D4Vinci/Scrapling | 98.1K | +6.9K | 65 | 1 day ago |
| Leonxlnx/taste-skill | 110.7K | +5.2K | 55 | 1 day ago |
| calesthio/OpenMontage | 77.2K | +4.2K | 40 | — |
| heygen-com/hyperframes | 79.6K | +4.1K | 45 | today |
| rohitg00/agentmemory | 29.9K | — | 64 | 19 days ago |
| Category median | 98.1K | +5.2K | 45 | — |
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