Aether Cache

Name: Aether Cache
Author: anishchugh05

by anishchugh05version 0.1.9i★ –iRuns on your computer

Registry nameio.github.anishchugh05/aether-cache

Install

Overview

Description from the maker (original English)

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

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Search & AI memory

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
The registry lists no key to fill in.

You need

PyPIPython’s uv installed (for the uvx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "aether-cache": {
      "command": "uvx",
      "args": [
        "aether-cache",
        "serve"
      ]
    }
  }
}

Run this in your terminal

claude mcp add aether-cache -- uvx aether-cache serve

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "aether-cache": {
      "command": "uvx",
      "args": [
        "aether-cache",
        "serve"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "aether-cache": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "aether-cache",
        "serve"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account anishchugh05, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Search & AI memoryi

More stars than 0% of the other 7241 servers in this category
Published to the registry more recently than 68% of the other 7241 servers in this category
Basic checks equal to or better than 100% of the other 7241 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Aether Cache safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.1.9) reached the registry 18 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Context7, Codebase Memory, Exa

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Context7

by upstash

Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

Computer or cloud★ 64,224MITUpdated 3 days ago

Install

Codebase Memory

by DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

Runs on your computer★ 48,148MITUpdated 20 days ago

Install

Exa

by exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

Runs in the cloud★ 5,213MITUpdated 44 days ago

Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

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:

Layer	What it adds
MCP server	Claude Code, Cursor, and any MCP tool share one memory
Git awareness	Memories retire themselves when the code they describe changes
Memory layer	Status, provenance, full history, duplicate merging, and conflict review, inside the engine
HNSW vector index	Semantic search: 99.4% recall at 0.84 ms on 100K vectors, 22× faster than exact search
Redis-compatible engine	RESP protocol, 50+ commands, replication, transactions, and crash-safe persistence (0 acknowledged writes lost across 1,039,890 writes and 8 `kill -9` crashes), at 88–93% of real Redis's throughput

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.

Setup	Tasks done right	Across sessions	Avg cost per task
No memory	43% (9 of 21)	3 of 6	$0.12
CLAUDE.md notes, same facts	90% (19 of 21)	4 of 6	$0.12
Mnemolith, same facts	100% (21 of 21)	6 of 6	$0.14

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.

Command	What it does
`mnemolith setup`	One-time setup: engine, model, and AI tools
`mnemolith add`	Adds the repo you're in (or a path) so the dashboard can check its files; the dashboard can also find and add repos for you
`mnemolith ui`	Opens the dashboard: see what your AI remembers, and confirm, fix or retire memories whose files changed
`mnemolith import`	Turns the notes in `CLAUDE.md`, `AGENTS.md`, and Cursor rules into memories; shows them first and asks
`mnemolith remove`	Removes a project (default: the one you're in), like Remove project in the dashboard: its memories are retired, not deleted
`mnemolith export`	Saves memories, with their linked files and history, to a JSON file (`-p` for one project)
`mnemolith status`	Is it running, and what's in this project's memory
`mnemolith doctor`	Checks everything and tells you how to fix what's wrong
`mnemolith list` / `recall "query"` / `explain m1`	Look at memories from the terminal
`mnemolith sync`	Writes current memories into `AGENTS.md` / `CLAUDE.md`
`mnemolith mender on` / `off`	Turns Mender on or off; `mnemolith mend` drafts fixes for this repo now
`mnemolith connect cursor`	Connects one tool: `claude-code`, `claude-desktop`, `cursor` or `codex` (`--print` shows config for any other MCP tool)
`mnemolith start` / `stop`	Runs or stops the engine (it also starts on its own when a tool needs it)
`mnemolith uninstall`	Disconnects your AI tools, stops the engine, and asks before deleting memories

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

Only the beginning is shown; read the rest in the repo

Aether Cache

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Search & AI memoryi

Common questions

Alternatives

Context7

Codebase Memory

Exa

README from the maker

Mnemolith

Not a Redis clone

Does it help?

What it looks like

Quick start

Mender: drafted fixes for stale memories