ember

Name: ember
Author: shapeandshare

by shapeandshareversion 0.16.0i★ –iRuns on your computer

Registry nameio.github.shapeandshare/ember

Install

Overview

Description from the maker (original English)

Calibrated advice for coding agents: typed questions in, probabilities out. Apple Silicon.

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: Other
You need to fill in: EMBER_AUTH_TOKEN

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).
You fill in yourself: EMBER_SERVER_URL, EMBER_AUTH_TOKEN

Values marked secret are keys to your account. Never share them or paste them into a chat.

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": {
    "ember": {
      "command": "uvx",
      "args": [
        "ember-advise",
        "mcp"
      ],
      "env": {
        "EMBER_SERVER_URL": "your-value",
        "EMBER_AUTH_TOKEN": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add ember --env EMBER_SERVER_URL=your-value --env EMBER_AUTH_TOKEN=your-value -- uvx ember-advise mcp

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

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

{
  "mcpServers": {
    "ember": {
      "command": "uvx",
      "args": [
        "ember-advise",
        "mcp"
      ],
      "env": {
        "EMBER_SERVER_URL": "your-value",
        "EMBER_AUTH_TOKEN": "your-value"
      }
    }
  }
}

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": {
    "ember": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "ember-advise",
        "mcp"
      ],
      "env": {
        "EMBER_SERVER_URL": "your-value",
        "EMBER_AUTH_TOKEN": "your-value"
      }
    }
  }
}

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.

Values you fill in

EMBER_SERVER_URL env
Inference endpoint; defaults to the local model server at http://127.0.0.1:8765
EMBER_AUTH_TOKEN secret env
Credential for a remote inference endpoint

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 shapeandshare, 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 Otheri

More stars than 0% of the other 32424 servers in this category
Published to the registry more recently than 62% of the other 32424 servers in this category
Basic checks equal to or better than 100% of the other 32424 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 ember 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?

You need to fill in: EMBER_AUTH_TOKEN

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 (0.16.0) reached the registry 23 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: Spec Driven Development, Remote Desktop Commander, BankBridge

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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.

A gut feeling for coding agents. AI coding assistants like Claude Code, Codex, opencode, and Kilo Code constantly have to decide: start now or ask a question first? Is this test failure real? Is this change safe to push? ember is a small add-on that gives them a quick second opinion at those moments, as a number ("93% likely this needs review"), so they stop interrupting you needlessly and stop making risky changes without asking. You don't call it yourself; your assistant does. It's free and open source, and you choose where the model runs: on your Apple Silicon Mac (32 GB of memory or more, a one-time ~18 GB download), on a server you host, or on one your team already runs. ember advises; the agent decides.

Under the hood, ember runs Cloudflare's Clef-Flash decision model, from its public Hugging Face repo, and exposes it as one MCP tool, advise, that returns a calibrated probability for every option.

Website: shapeandshare.github.io/ember

Ways to run ember

All three are supported equally; ember init asks which one you want.

	On your Mac	On a server you host	On a server someone else runs
Where the model runs	your Apple Silicon Mac	a Mac or an NVIDIA GPU machine you run	wherever its operator runs it
Where your requests go	nowhere: they stay on your Mac	your server	that server
What you need	32 GB of memory, ~18 GB of disk	the server: as for local, or a CUDA GPU; clients: only its address	its address, and a token if it asks for one
Set up with	`ember model pull`, then `ember init`	Remote inference or Hosted deployment	`ember init --server-url URL`

Nothing is ever sent to a server you didn't configure. Without a terminal to ask (a script, CI), ember init sets up local inference; --local or --server-url answer the question up front.

How it works

A decision model is not a chat model: it takes a state plus a schema of typed questions and returns one probability per option, with no text generation. So ember plugs into agents as a tool, while their reasoning stays on their normal LLM:

The model server (ember/serving/server.py) loads the model once and stays warm across agent sessions.
The MCP server (ember/mcp/mcp_server.py) never loads the model; it starts the model server on the first tool call, so the MCP handshake stays instant.

Names

Thing	Name
Product, Python import, repository	`ember`
Distribution (`uv tool install`, PyPI)	`ember-advise`, because `ember` is taken on PyPI and `gut` is held by an empty project
CLI	`ember` (short alias: `gut`; `ember-advise` too, so `uvx ember-advise mcp` works)
MCP server / command	`ember` / `ember-mcp`
Tool	`advise` — opencode: `ember_advise`; Claude Code: `mcp__ember__advise` (plugin: `mcp__plugin_ember_ember__advise`); Kilo Code: `ember_advise`
Playbook skill / MCP resource	`ember-advise` / `ember://guide`
Environment variables	`EMBER_*`

"Clef" always refers to Cloudflare's upstream model, never to this product. Select a model with ember model pull / EMBER_MODEL= ; run ember model list to see every registered entry (flash, full).

A hosted deployment (e.g. Outerbounds) that supplies the model's S3 location directly at start time doesn't use this registry at all — see "Hosted deployment: a model location supplied at start time" below.

Verified

Tested versions and hardware are in COMPATIBILITY.md. Current accuracy and latency, from the latest tracked benchmark run, are on the benchmark report.

Install (Apple Silicon)

Requirements

To use a server someone else runs, you need only Python 3.12 (managed by uv) and the server's address; skip ember model pull. To run the model yourself:

Apple Silicon Mac (M-series) on macOS for local use (MPS). Intel Macs remain out of scope. For a hosted deployment on NVIDIA/CUDA compute (e.g. Outerbounds), see "Hosted deployment" below and deployment/README.md.
Unified memory above the model's size: 32 GB or more for flash (9B), 96 GB or more for full (27B). Only 128 GB has been verified.
Disk: about 18 GiB for flash or 55 GiB for full, in Hugging Face's shared cache (~/.cache/huggingface). Config, state, and logs live in ~/Library/Application Support/ember.
Python 3.12, managed by uv.

uv tool install --python 3.12 ember-advise

ember model pull # ~18 GB, resumable, disk-space checked ember doctor # platform, dependencies, model, server, and agent registration ember init --opencode --global # register with opencode for every repo on this machine

Keep --python 3.12: uv otherwise picks your newest interpreter, which the pinned torch/transformers stack is not tested on.

This installs the latest released wheel from PyPI.

To pin a specific release tag from GitHub instead (no PyPI required):

uv tool install --python 3.12 "ember-advise @ git+https://github.com/shapeandshare/ember@v0.16.0"

The repository is public, so the git install needs no credentials. To use SSH instead, install from git+ssh://git@github.com/shapeandshare/ember@v0.16.0.

If you manage Python with conda, mamba, or pixi, install the same tool from the interim joshburt channel on Anaconda.org (it moves to conda-forge once that feedstock lands):

conda install -c joshburt -c conda-forge ember-advise   # mamba and pixi take the same flags

Installed ember before the rename, as gut? Run uv tool uninstall gut first: both distributions provide the same commands.

Restart opencode and every repo on this machine gains ember_advise. The model server stays lazy — it starts on the first tool call (or with ember start).

Per-project skill and policy (run once in each repo you want ember-aware agents):

cd /path/to/your/repo

ember agents install --agent opencode # installs the ember-advise playbook skill ember agents show snippet >> AGENTS.md # then edit the project policy block at the end

The skill teaches the agent *when* to consult ember and *how* to ask; the AGENTS.md snippet adds a project-specific policy you customize (e.g. "check change risk before every push"). See Agent onboarding below for all harnesses and options.

flash targets the commit verified on MPS (17f0b0a) and full its release commit (2f3de3d, not yet verified locally) as a download convenience, and torch/torchvision are pinned to the tested minor series — but ember does not restrict itself to a hand-maintained allowlist of individually verified weights; it runs any model that fits its loader contract (constitution Article V, "Model Loading"). Set EMBER_MODEL_DIR to run another weights directory.

Cloud

ember is Apple-Silicon-first locally, and supports NVIDIA GPUs for hosted deployment (constitution Article VI, "Apple Silicon and CUDA") — three devices total: run it on an Apple Silicon host with the memory above (MPS), on an NVIDIA GPU host (EMBER_DEVICE=cuda, float16 — see "Hosted deployment: a model location supplied at start time" and deployment/README.md for a full Outerbounds example), or on any host with the CPU fallback (EMBER_DEVICE=cpu — float32, roughly twice the memory, much slower). The HTTP server binds to loopback by default; to serve other machines set EMBER_HOST and set EMBER_SERVER_AUTH_TOKEN to require Authorization: Bearer (or any header name via EMBER_AUTH_HEADER, e.g. x-api-key, on the client side). Ember does not terminate TLS — front a remote-serving deployment with a proxy. Clients point at it with EMBER_SERVER_URL. See COMPATIBILITY.md and SECURITY.md.

Agent onboarding

Installing the tool is half the job; the other half is making agents want to consult it at the right moments and read its answers sensibly. ember/agent_kit/ ships that guidance through every channel each agent actually reads:

Channel	opencode	Kilo Code	Claude Code	Codex CLI	How you get it
MCP server instructions (when to consult, how to ask, how to read answers)	✅ in the system prompt	✅ in the system prompt	✅ (2 KB cap)	—	built in, nothing to do
`ember://guide` resource (full playbook)	✅ via `read_mcp_resource`	✅ via `read_mcp_resource`	✅	—	built in
`ember-advise` skill (playbook, loaded on demand)	✅	✅	✅	✅	`ember agents install --agent`
AGENTS.md / CLAUDE.md policy block	✅	✅	✅ (CLAUDE.md)	✅	`ember agents show snippet >> AGENTS.md`

ember init --opencode                  # opencode: config entry, plugin, and skill

ember init --kilocode # Kilo Code: kilo.json entry and skill ember init --codex # Codex CLI: .codex/config.toml entry and skill ember agents install --agent claude # .claude/skills/ember-advise/SKILL.md ember agents install --agent codex # .agents/skills/... (opencode reads this too) ember agents show snippet >> AGENTS.md # then edit the project policy at the end

The skill is a playbook, not a reference card: the decision points worth consulting ember about, copy-paste question sets for intent and readiness, failure triage, change risk, routing, and effort, and starting confidence thresholds calibrated from observed model output (re-measured whenever the pinned model revision changes). The snippet ends with a project policy — edit it to wire ember into your own workflow, e.g. "check change risk before every push".

Agent-specific notes:

opencode reads skills from .opencode/skills, .claude/skills, and .agents/skills, so install one copy per project to avoid duplicate listings.
Kilo Code: ember init --kilocode writes the mcp.ember entry to kilo.json (same config shape as opencode) and installs the skill to .kilo/skills/ember-advise/SKILL.md; the tool appears as ember_advise. Kilo Code also reads AGENTS.md automatically.
Claude Code: register the server with claude mcp add --scope user ember -- ember-mcp (every project; drop --scope user to register it for the current project only); the tool appears as mcp__ember__advise. Or install the ember plugin, which bundles the MCP entry and the ember-advise skill (so skip ember agents install --agent claude):

  claude plugin marketplace add shapeandshare/ember

claude plugin install ember@ember

The plugin still runs the ember-mcp you installed with uv tool install, and its tool appears as mcp__plugin_ember_ember__advise. Use one route, not both, or the tool is listed twice.

Codex CLI: ember init --codex writes [mcp_servers.ember] to .codex/config.toml (--global: ~/.codex/config.toml, or $CODEX_HOME/config.toml) and installs the skill to .agents/skills/ember-advise/SKILL.md. Codex loads a project .codex/config.toml o

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

ember

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

Values you fill in

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 Otheri

Common questions

Alternatives

Spec Driven Development

Remote Desktop Commander

BankBridge

README from the maker

Ways to run ember

How it works

Names

Verified

Install (Apple Silicon)

Requirements

Cloud

Agent onboarding