Aether Cache

Mnemolith

Shared memory for AI coding tools that stays true to your code.

*Mnemolith (NEE-mo-lith): "memory stone." What your AI learns, carved where every tool can read it. (Why the name)*

Formerly Aether Cache. If you installed aether-cache, see Moving from Aether Cache: your memories come with you.

[Website](https://mnemolith.dev/) · [PyPI](https://pypi.org/project/mnemolith/)

Claude Code, Cursor, and other AI tools each forget your project between sessions, and when they do remember things, nothing checks whether those memories are still correct. Mnemolith gives every tool one shared, local memory, and keeps it honest:

• Memories go stale when the code changes. Each memory is linked to the files it's about, with a snapshot of their git content hash. When docker-compose.yml changes, the memory about it is retired automatically instead of being fed to your AI forever.
• Contradictions get replaced, not hoarded. "We migrated to MySQL" retires "we use Postgres" instead of sitting next to it and confusing the model. Near-identical repeats are merged.
• Every memory can explain itself. Which tool and session saved it, which file versions it was based on, and every change since: created, seen again, went stale, confirmed, replaced.
• It works with the files you already use. Current memories sync into a managed section of AGENTS.md and CLAUDE.md, so they're committed, reviewed in PRs, and visible to teammates who don't run Mnemolith.

It runs entirely on your machine, on top of a database engine I wrote from scratch.

Not a Redis clone

Mnemolith started as a from-scratch rebuild of Redis in Java, then kept going. Every layer here is written from scratch, and each one does something the layer beneath it can't:

The bottom layer alone is a working Redis: redis-cli, redis-benchmark, and redis-py talk to it unchanged. The memory layer, git awareness, and MCP server are things Redis doesn't do at all.

Claude Code ─┐                       ┌─────────────────────────────────────────────┐

Cursor ──────┼─ MCP ─► mnemolith ─┼─ RESP ─► Java engine (Main.java) │ other tools ─┘ (Python: embeddings,│ memories, HNSW vector index, │ git hashing, sync) │ history, append-only file on disk │ └─────────────────────────────────────────────┘

Does it help?

We tested it. Claude Code did 7 tasks in a sample codebase, 3 times each, in three setups. Every task needs something only a teammate would know: a past decision, who owns which code, a promise to a partner, a business rule. Two need a fact mentioned in an earlier session. An automatic check grades every run.

Without memory, Claude edited another team's code, changed a frozen partner API and skipped refund approval, every time. A CLAUDE.md file held the same facts but missed a database address mentioned in an earlier session 2 times out of 3; Mnemolith saved it on its own and used it next session. The cost is about 15% more per task than a notes file, at API prices, because recalling and keeping memories up to date takes a few extra turns. 63 runs on Claude Opus 5.5, November 2026. In an earlier round where every fact could also be found in the code, all three setups tied.

Run it yourself (uses your own Claude Code plan; see eval/ for what each task checks):

cd eval && python3 run.py --repeat 3 && python3 report.py

What it looks like

The dashboard (mnemolith ui): memories whose files changed wait for a decision, with the file versions side by side.

And from your AI tool's side, a memory linked to a file, the file changes, and the next lookup catches it:

> remember("The database runs Postgres via docker compose", files=["docker-compose.yml"])

Saved as m1.

... someone edits docker-compose.yml ...

recall("database setup")

These memories were just retired because files they depend on changed. If one is still true, call confirm_memory; if it's wrong, save the corrected fact with remember: [m1] "The database runs Postgres via docker compose" is now marked outdated: docker-compose.yml changed.

confirm_memory("m1") # still true, so re-link it to the new version of the file

Confirmed m1; it's active again and linked to the current file versions.

explain_memory("m1")

m1: "The database runs Postgres via docker compose" status: active, project: demo saved by: claude-code (session eea54b5c) linked files: docker-compose.yml@02ea346... history: 19:16 created: by claude-code (session eea54b5c), linked to docker-compose.yml@87da641... 19:16 active -> stale: docker-compose.yml changed since this was saved 19:16 re-linked: to docker-compose.yml@02ea346... (confirmed still true) 19:16 stale -> active: confirmed still true

A newer fact replacing an older one:

> remember("The API timeout was raised to 60 seconds")

Saved as m3. Related existing memories: [m1] (similarity 0.58) The API timeout is 30 seconds If m3 makes any of these no longer true, call replace_memory(old_id, "m3"). Otherwise do nothing.

replace_memory("m1", "m3")

m1 retired; m3 replaces it.

Quick start

One line installs everything and runs setup. On macOS or Linux:

curl -fsSL https://mnemolith.dev/install.sh | sh

On Windows (PowerShell):

powershell -ExecutionPolicy ByPass -c "irm https://mnemolith.dev/install.ps1 | iex"

The installer (install.sh, install.ps1) gets uv if you don't have it (uv brings Python), installs Mnemolith, and runs mnemolith setup. Prefer your own tools? Any of these works, followed by mnemolith setup:

uv tool install mnemolith

pipx install mnemolith pip install mnemolith # Python 3.10+

setup starts the engine in the background, downloads the embedding model once (about 90 MB), and connects every supported AI tool it finds on your machine: Claude Code, Claude Desktop, Cursor, and Codex. That's it. Open your AI tool in any git repo and try:

Remember that our tests need DOCKER_HOST set. It depends on docker-compose.yml.

Then start a new session and ask how to run the tests.

Only use Claude Code? You can install Mnemolith as a plugin instead, with no setup step (needs uv):

/plugin marketplace add anishchugh05/mnemolith

/plugin install mnemolith@mnemolith

The plugin (plugin/) runs the same server and adds a /mnemolith:dashboard command. Use the plugin or setup, not both, or Claude sees the tools twice.

The engine runs on Java 11+. If you have it, it's used. If you don't, Mnemolith downloads a private copy (about 50 MB) into ~/.mnemolith/java, checks it against its published checksum, and uses it only for Mnemolith; nothing is installed system-wide, and mnemolith uninstall removes it.

Already keep notes for your AI in CLAUDE.md, AGENTS.md, or Cursor rules? Run mnemolith import in the repo (or use Import notes in the dashboard) to turn them into memories, linked to the files they mention.

Memories are kept per project (the git repo's folder name), so projects never mix. Everything stays on your machine: the engine only accepts connections from it, and your memories live in ~/.mnemolith.

If mnemolith isn't found after installing, run uv tool update-shell and open a new terminal. Port 7380 taken? Set MNEMOLITH_PORT and run setup again. To uninstall: mnemolith uninstall, then uv tool uninstall mnemolith.

Mender: drafted fixes for stale memories

Flagging a stale memory is half the job: someone still has to work out what's true now and type it in. Mender, an optional part of Mnemolith, drafts that for you. mnemolith setup asks whether to turn it on; mnemolith mender on (or Settings in the dashboard) changes it later. It needs no API key and installs nothing extra.

• Simple changes are drafted by plain rules, on your machine. Mender compares the version of each file the memory was saved against (from git) with the file now. image: postgres:16 became image: mysql:8, so "The database is Postgres (postgres:16 image)" becomes "The database is MySQL (mysql:8 image)". It handles version bumps, moved files (the path is updated, not treated as a deletion), and changes that don't touch the memory at all (only a comment, or lines it doesn't mention), which it suggests confirming as still true.
• Everything else is drafted by the AI tool you already use. With Mender on, Claude Code, Cursor, and Codex get two more tools: list_stale shows each stale memory with what changed in its files, and propose_fix submits a draft. Drafts are chec