I kept running into a freaking issue with agent workflows.
I’d spend time getting one setup dialed in — prompts, preferences, project rules, repo context, workflow notes — then jump from Hermes to OpenClaw, NanoClaw, Claude Code, Cursor, Codex, Goose, Warp, whatever… and I’d end up explaining the same stuff again.
That gets old fast.
So I built Memory Hive.
Not another agent. Not a replacement for Hermes, OpenClaw, or NanoClaw. Not some “the agents magically train themselves” thing.
It’s boring on purpose: local memory infrastructure for all your agents.
The idea is simple:
- Each agent gets its own private memory silo.
- All agents can also read from a shared hive.
- Raw notes stay separate from curated knowledge.
- A curator role helps promote useful lessons and catch conflicts.
- Everything lives in local Markdown files, so you can inspect it, edit it, grep it, diff it, or version it.
That last part matters.
Patience is key with agent memory. If you just dump everything into a folder and call it “long-term memory,” you don’t get intelligence. You get a junk drawer full of stale assumptions.
Memory Hive is meant to keep the useful stuff:
- Project decisions
- Repo conventions
- Recurring mistakes
- Workflow preferences
- Cross-agent notes
So if I train my Hermes setup on a useful workflow, OpenClaw or NanoClaw should be able to benefit from the distilled version later. If Claude Code learns a repo convention, Codex or Cursor should not need to rediscover it from scratch.
It supports a bunch of platforms, including:
OpenClaw, NanoClaw, Hermes, Claude Code, Cursor, Continue, Gemini CLI, Goose, Amazon Q, OpenHands, Roo, Kilo, Windsurf, Warp, Sourcegraph Amp, OpenAI Codex CLI, OpenCode, Aider, Cline, Zed, Crush, and GitHub Copilot.
Install:
```bash
curl -fsSL memoryhive.neural-forge.io/install.sh | sh
```
Default location:
```bash
~/.memory-hive
```
This is not pretending to solve memory perfectly.
Agents still forget.
Agents still remember the wrong thing.
Agents still carry stale context forward.
Memory Hive is my attempt to make that mess more manageable:
Private memory where it should stay private. Shared memory where it actually helps. Curation so the hive does not rot.
Project: https://memoryhive.neural-forge.io
Repo: https://github.com/TJCurnutte/memory-hive
Appreciate some stars!
Test it out, let me know what you think!!!