Local-first memory layer for AI coding agents — Markdown as source of truth, MCP server + CLI, human-reviewed capture, team knowledge via git PRs.
View on GitHub ↗Homepage ↗A shared organizational memory layer that helps people and AI capture, retain, and reuse institutional knowledge.
Local-first persistent memory for AI coding agents: an opencode plugin plus a generic MCP server (VS Code Copilot, Cursor, Claude Code, Visual Studio, …).
Engineering knowledge lives in two places: the code, and people's heads. Every new AI coding session starts from zero — the same project context gets explained again, the same gotchas get rediscovered, the same incident lessons fade when the chat ends.
open-memex captures the part worth remembering — the decision, the constraint, the lesson — as reviewable Markdown, and injects it back into the next session automatically.
Most developers don't use one AI tool — they use several on the same machine: Copilot in VS Code, Cursor, opencode, Claude Code. Each tool keeps its own silo: a decision made in one is invisible to the others.
open-memex is tool-agnostic by design. Memory lives as Markdown + SQLite next to your project, and every editor talks to it through the same MCP interface. Wire up two, three, five clients with open-memex init — they all read and write the same memory on that machine. A constraint captured in VS Code is respected in opencode; a lesson learned in Cursor shows up in Claude Code.
Your memory belongs to you — not to your tools.
It also complements agentic development workflows (spec-driven development, plan/implement/verify loops): plans produce decisions, verification produces rules — open-memex is the memory layer that keeps them across sessions instead of re-deriving them on every
From the project README.
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