angelnicolasc

angelnicolasc / graymatter

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Three lines of code to give your AI agents persistent memory. Reduce 90% token consumption while also maintaining quality.

agent-memory ai-agents ai-tools claude-code cli
32
8
100% credibility
Found Apr 17, 2026 at 32 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Go
AI Summary

GrayMatter is an open-source Go library and command-line tool that provides persistent, efficient memory storage for AI agents to recall relevant facts and reduce token consumption.

How It Works

1
🔍 Discover GrayMatter

You hear about a simple tool that lets your AI helpers remember important details from past chats, making them smarter without wasting space.

2
📥 Download the program

Grab the ready-to-use program for your computer with a quick download, no complicated setup needed.

3
⚙️ Set it up in your folder

Place it in your work folder and run a quick start command to create a memory space just for your projects.

4
💾 Teach it memories

Tell the tool what to remember, like 'user likes short answers' or 'next step is Friday follow-up', and it saves them safely.

5
🧠 Recall smart facts

Ask it to pull up the most relevant memories for your current task, and it hands you just what your AI needs.

🎉 AI gets a real memory

Your AI helper now remembers everything important, responds better, and uses way less effort on every chat.

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Star Growth

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AI-Generated Review

What is graymatter?

Graymatter is a Go library and CLI that gives AI agents persistent memory in three lines of code, storing observations like user preferences and recalling relevant facts for queries. It cuts token usage by 90% versus full-history prompts by injecting only top matches, working offline with a single binary—no Docker, databases, or cloud setup. Supports Ollama, OpenAI, or Anthropic embeddings, plus keyword fallback, and hooks into Claude Code/Cursor via MCP tools like memory_search and memory_add.

Why is it gaining traction?

It fills Go's gap for embeddable agent memory, unlike Python/TS options needing servers—pure binary deploys anywhere, with CLI commands for remember/recall, checkpoints, and TUI views. Token benchmarks prove real savings at scale, and REST server/metrics make it observable. Extras like shared namespaces, knowledge graphs, and Obsidian exports appeal to devs eyeing graymatter robotics or graymatter superfood cognitive support for agents.

Who should use this?

Go devs building stateful AI agents for sales automation, customer support bots, or CLI tools that need recall without bloat. Backend teams using Anthropic APIs who hate token burn on long sessions. Cursor/Claude Code users in Go projects wanting memory_reflect for self-editing agents, or graymatters health trackers persisting user data.

Verdict

Grab it for Go AI prototypes—three lines model works as promised, with strong docs, CLI polish, and 73.5% test coverage. But 32 stars and 1.0% credibility score flag early maturity; productionize only after your own benchmarks.

(198 words)

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