Your OpenCode agent shouldn't rediscover the same decisions every session — Mind v1.7 is here

A few months ago, I introduced Mind here as a persistent memory system for OpenCode.

The original frustration was simple: every time a long coding session ended, the next agent often had to reconstruct the reasoning behind the work.

Why did we choose this architecture? Which fixes had already been tried? What was the next step?

Mind v1.7.0 is now out, and the project has become a much more complete memory and continuity system.

Mind uses a local SQLite database to preserve useful context across sessions. OpenCode can access it through MCP, while the managed integration helps capture and recover session knowledge.

The big changes in this release:

• Better retrieval: full-text, fuzzy, substring, and phrase search work together, with optional embeddings.
• 86.67% answer accuracy on a stratified 120-question OmniMemEval test without RAG. Not an official leaderboard comparison.
• Improved continuity: checkpoint completion and session summaries are now handled more reliably.
• A new web experience: inspect memories, search project knowledge, and explore their relationships in Neural Map.
• Simpler setup: a shared memory-management skill and streamlined agent configuration.

The goal isn't to dump your entire history into context. It's to preserve useful knowledge and retrieve what's relevant when the agent needs it.

Install from GitHub, then:

mind setup opencode

Already installed? Run mind update and restart OpenCode.

Project: https://github.com/GabrielMartinMoran/mind

v1.7.0: https://github.com/GabrielMartinMoran/mind/releases/tag/v1.7.0

Mind is open source, MIT licensed, and local-first.

If you've been using persistent memory with OpenCode, I'm interested in what works well for you and where retrieval still fails.