zero8dotdev

zero8dotdev / smriti

Public

Shared memory for AI-powered engineering teams. Captures, indexes, and recalls conversations across Claude Code, Cursor, Codex, and other agents. Share team knowledge through git — no cloud required.

ai-agents bun claude-code codex cursor
20
3
100% credibility
Found Feb 12, 2026 at 11 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
TypeScript
AI Summary

Smriti captures, indexes, and enables searching of conversations from AI coding tools like Claude Code and Cursor, allowing teams to share knowledge locally through git repositories.

How It Works

1
🔍 Discover Smriti

You hear about Smriti when frustrated that your AI coding helpers forget everything from yesterday or what teammates figured out.

2
⚙️ Set it up quickly

With one easy step, you add Smriti to your computer so it can start remembering your work automatically.

3
💾 Work with AI as usual

As you chat with your AI coding buddy like Claude or Cursor, Smriti quietly saves every conversation in the background without interrupting you.

4
🧠 Recall past wisdom

Next time, just ask Smriti 'what did we learn about auth?' and it pulls up the best insights from all your saved chats, saving hours of repeat work.

5
📤 Share with your team

Tell Smriti to package the key memories into your project's shared folder, ready for everyone to grab via their usual update routine.

6
📥 Teammates get the memories

Your coworkers pull the updates and run a quick sync, instantly gaining your hard-won knowledge in their own setup.

🎉 Team supercharged

Now everyone starts with full context, decisions stick around, and your team ships faster without losing brilliant ideas to forgotten chats.

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AI-Generated Review

What is smriti?

Smriti is a local shared memory layer for AI coding agents like Claude Code, Cursor, and Codex, capturing team conversations automatically, indexing them in SQLite, and enabling fast recall via CLI commands like `smriti recall "auth migration"`. It solves the amnesia problem where agents forget prior decisions, duplicated work, and architectural insights across sessions and teammates. Built in TypeScript with Bun, it uses git for github shared repository knowledge—no cloud, just commit `.smriti/` folders for shared github workflows.

Why is it gaining traction?

Unlike cloud vector stores, smriti runs fully local with hybrid full-text and semantic search, auto-categorizing sessions into trees like "decision/technical" for precise filtering. Token compression turns 20k tokens of history into 500 via synthesis, and git-based sharing beats shared github actions or runners by embedding metadata in markdown frontmatter. Developers hook it instantly with one curl install, hooking Claude Code sessions without workflow changes.

Who should use this?

Engineering teams building with AI agents daily, especially those debugging auth flows or debating architectures repeatedly. Backend devs on shared github projects tired of re-explaining rate limiting strategies, or frontend squads syncing Cursor insights across PRs. Ideal for small remote teams avoiding shared memory ipc pitfalls or cloud vendor lock-in.

Verdict

Try smriti if AI coding feels fragmented—its CLI and git sharing deliver immediate wins despite 10 stars and 1.0% credibility score signaling early maturity. Docs are thorough with uninstall script, but run A/B tests via `smriti compare` to validate token savings before team rollout.

(198 words)

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