KnowledgeMay 12, 2026·3 min read

remindb — Portable Memory DB for AI Agents

remindb stores agent memory in a SQLite file with search and deltas. Install via a one-line script and serve memory to MCP-capable agents.

Agent ready

This asset can be read and installed directly by agents

TokRepo exposes a universal CLI command, install contract, metadata JSON, adapter-aware plan, and raw content links so agents can judge fit, risk, and next actions.

Needs Confirmation · 62/100Policy: confirm
Agent surface
Any MCP/CLI agent
Kind
Memory
Install
Script
Trust
Trust: Established
Entrypoint
curl -fsSL https://raw.githubusercontent.com/radimsem/remindb/main/install.sh | bash
Universal CLI install command
npx tokrepo install 44676243-5f9f-5ae0-85c4-c8543950d448
Intro

remindb is designed to keep memory lightweight and portable: one .db file you can copy, commit, or sync, while the agent queries it via fast search and deltas instead of rereading everything.

Best for: Long-running agents that need persistent memory across sessions and machines

Works with: Linux/macOS/Windows; install scripts; SQLite-backed storage

Setup time: 10–20 minutes

Key facts (verified)

  • README provides a one-line install script for Linux/macOS and a PowerShell installer for Windows.
  • From source build notes Go 1.26+ in README.
  • GitHub: 89 stars · 3 forks; pushed 2026-05-12 (GitHub API verified).

Main

For best results, treat memory as a product surface:

  • Decide what should be written (decisions, preferences, constraints) and what should not (raw logs, secrets).
  • Periodically compact and summarize cold memory nodes so search stays fast and relevant.
  • Use delta-based sync (cursor hashes) to keep the agent “caught up” without large token spends.

README excerpt (verbatim)

remindb logo

remindb

Agentic memory in a single SQLite file.
Stop letting your agent re-read the same notes every session.

CI Latest release License Go version


remindb architecture

Why I built this

Coding agents already have memory. CLAUDE.md, AGENTS.md, your notes folder, that growing pile of project READMEs. Stuff persists just fine.

The problem is how the agent consumes it. Every session starts by re-reading the whole pile from scratch — every Read, every Grep, scanning raw prose the agent has already processed dozens of times. Big context windows don't fix it. A 1M-token window is still paid per call, and still can't tell yesterday's stale note from today's relevant one.

Raw markdown is the wrong shape for memory. Not because it can't hold the words — it can — but because it forces the agent to pay full freight on every read.

remindb is a single SQLite file your agent treats as long-term memory. It parses your notes (Markdown, HTML, JSON, YAML, TOON) into a structured tree, hashes every node, encodes repetitive structures compactly when it saves tokens, and surfaces the whole thing through a tight MCP tool suite.

What you get

A tree the agent can index, not skim. Instead of ls-ing a folder and reading every file to orient, the agent calls MemoryTree once. Each entry is a typed node — [heading], [list], [kv], [table], [preamble], [text], [code], [embed] — with an ID, a short label, a temperature, and a token count. Think of it as ls -la for memory: one call, a scannable index, hot stuff floats up.

A real slice (from remindb inspect --tree):

[preamble] Preamble: framework, language, project (id=3kGXxidmWBp file=CLAUDE.md temp=0.50 tok=14)

### FAQ

**Q: Is remindb a server?**
A: README frames it as one portable SQLite file with an MCP runtime for fast queries.

**Q: How do I install it quickly?**
A: Use the provided install script for your OS, then verify with `remindb --version`.

**Q: Can I share memory across agents?**
A: Because it’s one `.db` file, you can copy/sync it, but you still need to manage access and privacy.
🙏

Source & Thanks

Source: https://github.com/radimsem/remindb > License: MIT > GitHub stars: 89 · forks: 3

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