Headroom

Name: Headroom
Author: Apertur3

by Apertur3version 0.2.20i★ –iRuns on your computer

Registry nameio.github.Apertur3/headroom

Install

Overview

Description from the maker (original English)

Live subscription limits, resets and budget checks for coding agents over MCP.

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

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

npmNode.js installed (for the npx 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": {
    "headroom": {
      "command": "npx",
      "args": [
        "-y",
        "headroomd",
        "mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add headroom -- npx -y headroomd mcp

Open in Cursor

Or copy the settings yourself

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

{
  "mcpServers": {
    "headroom": {
      "command": "npx",
      "args": [
        "-y",
        "headroomd",
        "mcp"
      ]
    }
  }
}

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": {
    "headroom": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "headroomd",
        "mcp"
      ]
    }
  }
}

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 7, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account Apertur3, 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 32691 servers in this category
Published to the registry more recently than 90% of the other 32691 servers in this category
Basic checks equal to or better than 100% of the other 32691 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 Headroom 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 (0.2.20) reached the registry 4 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, Dialyne

Alternatives

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

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by formulahendry

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Runs on your computer★ 440MITUpdated 14 months ago

Install

Remote Desktop Commander

by desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

Runs in the cloud★ 211Updated 2 days ago

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Dialyne

by dialyne

Real phone calls in France for AI agents: dial +33 numbers, menus, hold, AI disclosure.

Runs in the cloudUpdated today

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.

Your coding agents check their Claude and Codex limits before they start a job.

headroomd reads the 5-hour and weekly limits your subscriptions report and answers go, wait or reroute, over the CLI or MCP.

npm install -g headroomd   # or: brew install apertur3/tap/headroom

headroom setup headroom can claude-fable --owner me && echo go

Then install the Claude Code plugin (requires headroomd above):

claude plugin marketplace add Apertur3/headroom

claude plugin install headroom@headroom

macOS, Linux, Windows (experimental). No telemetry. Zero runtime dependencies.

Not related to headroomlabs-ai/headroom, the context-compression project.

Install

Node 22.13 or newer. The npm package is headroomd; the Homebrew formula is apertur3/tap/headroom. Both install the headroom command.

npm install -g headroomd

or, on macOS and Linux: brew install apertur3/tap/headroom

finds your logins, runs the doctor, asks before each change

headroom setup

one block per account: percent used, reset time and pace state per window

headroom

Claude usage comes from Claude Code's statusline. Add this to ~/.claude/settings.json (or the settings.json of each other profile), or chain an existing statusline with headroom statusline --chain ' ':

{ "statusLine": { "type": "command", "command": "headroom statusline" } }

Alongside it, Headroom runs Claude Code's own /usage at most every 10 minutes (it adds the scoped meters the statusline does not carry; the statusline never runs under claude -p, so it can go stale between runs). headroom doctor and headroom status say which is in use. Headroom never edits your Claude settings files.

For Claude Code, install the plugin after installing headroomd with npm or Homebrew:

claude plugin marketplace add Apertur3/headroom

claude plugin install headroom@headroom

It bundles the Headroom skill, the MCP server registration and a quota line on every prompt. Using it alongside headroom hook install does not print the quota line twice. See Claude Code plugin for requirements and uninstall commands.

Already running Claude Code or another agent? Copy skills/headroom/SKILL.md into its skills directory and say "set up headroom".

Without the plugin, headroom setup offers to register the MCP server for your default Claude Code profile. To register it by hand, or in another profile:

claude mcp add --scope user headroom -- headroom mcp

CLAUDE_CONFIG_DIR=~/.claude-work claude mcp add --scope user headroom -- headroom mcp

Agents without MCP, Codex for example, call the CLI. Then give your agents the instructions in For agents. The MCP tools and example calls are in docs/mcp-and-agents.md.

Manual setup and optional configuration

The three commands above are the short path. Discovery on its own:

headroom accounts discover   # finds Claude, Codex, Antigravity, Grok and Kimi logins

On macOS and Linux, brew install apertur3/tap/headroom installs the same package and adds a brew services start headroom service.

By hand, the same steps are one command:

headroom setup                # discovery, doctor, service, MCP registration -- asks before each change

Run headroom notify configure to choose notification channels, a preset and overrides. Run headroom update only when you choose to install a newer package; headroom uninstall reverses setup, and headroom completion prints a shell completion script.

accounts discover prints what it wrote (Wrote ~/.headroom/accounts.toml (4 accounts). Next: headroom doctor) and, the first time, seeds ~/.headroom/policy.toml and routing.toml from examples/ so headroom can --owner works immediately with the example action classes (claude-fable, codex-build, gemini-bulk) -- edit routing.toml to match your accounts.

Keep an optional second profile that is deliberately logged out without polling it: add enabled = false to its [[accounts]] block, or run headroom accounts disable . It remains configured and can be restored with headroom accounts enable .

Full walkthrough, including what each step grants and why: docs/quickstart.md.

status/doctor check the npm registry at most once a day (a plain GET of the headroomd version, no account data) and print a one-line notice when a newer headroomd is out; run headroom update (never automatic) to install it. Set update_check = false in ~/.headroom/policy.toml to turn the check off -- see Staying up to date.

For agents

Paste this into the CLAUDE.md or AGENTS.md your agents read, and replace the placeholders with your own action classes, meters and agent name. The agent then checks Headroom before it dispatches work, instead of asking you.

## Usage limits (Headroom)

Check Headroom before you start work on a subscription. Do not ask me about usage or reset times.

headroom can --owner : exit 0 means go, exit 2 means no. Any other exit is an error: treat it as no. Classes are the [consumes] entries in ~/.headroom/routing.toml.
On no, try the next class in your fallback list. If none has room, run headroom wait --meter --until-reset --max 6h (exit 3 means it timed out), then run headroom can again before you start anything.
Start a job with headroom run --meter --need : --owner -- , for example --need 5h:10 for 10 percent of the 5-hour window. It reserves the points, runs the command and releases them when it exits. Exit 2 means refused; otherwise it returns the command's own exit code.
UNKNOWN means there is no trustworthy reading. Treat it as no. Never pass --allow-unknown unless I ask for it.
For the full picture, read headroom --json, not the human view.
In Claude Code with the Headroom MCP server, quota_can answers the same question as headroom can.

To put live quota in front of the agent on every turn, run headroom hook install --agent claude (or answer yes in headroom setup). Each Claude Code prompt then carries one line the daemon wrote at its last poll, with its age, for about 60 tokens per turn; headroom line prints the same line for any agent. Claude Code on macOS and Linux only for now; Windows, Codex and Gemini hooks are not supported yet.

A plain can is advisory. A reservation tells other agents that use Headroom the points are taken; it does not limit what the job itself spends, and it cannot stop tools that do not use Headroom. The longer version, with pace states, leases and reserves, is skills/headroom/SKILL.md.

Platform support and known limitations

7 sources read 3 OSes tested in CI 1 local daemon, one call per decision 0 telemetry (one opt-out update check)

Sources: five subscription services (Claude, Codex, Kimi, and the experimental Antigravity and Grok) and two local server types (vLLM and llama.cpp). A stale or failed reading prints UNKNOWN , never a number. Full writeup · Reproduce it

Platform	Status
macOS	The primary platform: daily use on one machine, plus CI. Antigravity needs macOS 14 or later
Linux	CI on Ubuntu; cold install also checked by hand on ARM64
Windows	Experimental. Tests run in CI. On Windows 11, `headroom install-service` registers a "Headroom Daemon" task that starts immediately and serves a per-user named pipe whose name is a hash only. `headroom uninstall --home` asks the running daemon to shut down over that pipe, removes the task and the home, and exits 0. After an in-place upgrade, `headroom install-service` restarts the daemon onto the new version, except a daemon started by 0.2.6 or older, which has no shutdown request and must be stopped by hand once (end node.exe in Task Manager). Verified on Windows 11: MCP registration (`claude mcp add --scope user headroom -- headroom mcp` shows Connected) and a real Claude login read (fresh on the first poll). Not verified on Windows: a slow stop (the 27 second wait is covered by unit tests only) and start at logon and across reboots. Full detail below
Antigravity	Experimental. Depends on a private local endpoint that the vendor can change
Grok	Experimental. Reads the Grok CLI's undocumented chat-proxy endpoint and presents itself as the Grok CLI

The full table: tests, CI, install checks, Windows, vendor endpoints


Tests	`npm test` (vitest), run on every push on macOS, Ubuntu and Windows; some tests are POSIX-only and skip on Windows. Current counts are in the CI logs; method and limits: docs/verification.md
CI platforms	macOS, Ubuntu and Windows (`macos-latest`, `ubuntu-latest`, `windows-latest`): lint, tests, build, `npm pack --dry-run`, privacy sweep, `npm audit`
Daily use	one macOS machine; this is the only environment a person uses every day
Install from the packed tarball	scripted cold-install smoke test (`smoke-cold.sh`) runs in the release workflow; also checked by hand on macOS and on Linux ARM64
Windows	experimental. On Windows 11, `headroom install-service` registers a "Headroom Daemon" task that starts immediately and serves a per-user named pipe whose name is a hash only. `headroom uninstall --home` asks the running daemon to shut down over that pipe, removes the task and the home, and exits 0. After an in-place upgrade, `headroom install-service` restarts the daemon onto the new version, except a daemon started by 0.2.6 or older, which has no shutdown request and must be stopped by hand once (end node.exe in Task Manager). Verified on Windows 11: MCP registration (`claude mcp add --scope user headroom -- headroom mcp` shows Connected) and a real Claude login read (fresh on the first poll). Not verified on Windows: a slow stop (the 27 second wait is covered by unit tests only) and start at logon and across reboots. Earlier, 0.2.4 was installed on Windows 11 and `accounts discover`, `doctor`, `status` / `can` / `gate` / `dashboard` (UNKNOWN, never a fake number) and the HTML report permissions worked. The process watchdog is inactive on Windows. PowerShell's default execution policy blocks the `npm` and `headroom` `.ps1` shims; use `cmd`, or relax the policy

| W

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

Headroom

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 Otheri

Common questions

Alternatives

Spec Driven Development

Remote Desktop Commander

Dialyne

README from the maker

Install

or, on macOS and Linux: brew install apertur3/tap/headroom

finds your logins, runs the doctor, asks before each change

one block per account: percent used, reset time and pace state per window

For agents

Platform support and known limitations