contextburn

Name: contextburn
Author: arsentev-ai

by arsentev-aiversion 0.2.1i★ –iRuns on your computer

Registry nameai.arsentev/contextburn

Install

Overview

Description from the maker (original English)

Run efficiency for coding agents: share of paid tokens that became output, not context re-reading.

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

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": {
    "contextburn": {
      "command": "uvx",
      "args": [
        "contextburn",
        "mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add contextburn -- uvx contextburn mcp

Open in Cursor

Or copy the settings yourself

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

{
  "mcpServers": {
    "contextburn": {
      "command": "uvx",
      "args": [
        "contextburn",
        "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": {
    "contextburn": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "contextburn",
        "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 6, 2026

✓ Pass
Maker matches the repo
The registry name was verified against the domain arsentev.ai (the registry checks domain ownership)
… 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 32464 servers in this category
Published to the registry more recently than 41% of the other 32464 servers in this category
Basic checks equal to or better than 100% of the other 32464 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 contextburn 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 (0.2.1) reached the registry 2 months 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, yontu

Alternatives

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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.

contextburn reads the transcripts Claude Code already writes on your machine and tells you what share of the tokens you paid for became model output — and how much was the agent re-reading context it had already sent.

Token counters answer *"how much did I spend?"*. This answers *"how much of it was work?"* — a normalised share, so it can be compared across sessions, models and ways of working.

Try it

cp bin/contextburn ~/bin/contextburn && chmod +x ~/bin/contextburn   # python3 only, no dependencies

contextburn detail 24

Demo

Real output over the session logs of the 36 runs behind the U-curve report — nothing else on the machine. Video with DOI: 10.5281/zenodo.22713920. The runs themselves are open: Hugging Face (DOI 10.57967/hf/10366) · Kaggle · OSF (DOI 10.17605/OSF.IO/5QTWY).

Why two numbers

By tokens the share barely moves. Every agent step resends the accumulated context, so re-reading dominates whatever you do — it describes the agent.
Cost-weighted the share does move, because cached reads are priced far below fresh input and output. It depends on how you run sessions — it describes you.

The comparison above comes from a controlled experiment with its dataset and analysis scripts: Clear Every Third Task: A Measured U-Curve in the Context Economy of Coding Agents.

How it counts

Reads local Claude Code transcripts (~/.claude/projects/**/*.jsonl). Nothing leaves the machine — no network calls at all.
Deduplicates usage records by message id and keeps the element-wise maximum. A streaming runtime writes an early snapshot and a final record for the same call: counting both double-counts it, keeping only the first halves the output.
Weights the cost share with per-model prices kept at the top of bin/contextburn. Update them there when they change.

Commands

command	what it shows
`contextburn`	what is burning tokens right now
`contextburn detail [hours]`	run efficiency, sessions, and what specifically inflated the context
`contextburn window`	the current 5-hour subscription window
`contextburn --json`	machine-readable state (used by the menu-bar app)
`contextburn --probe`	raw JSON dump of the parsed sessions
`contextburn --efficiency [hours]`	run efficiency as JSON
`contextburn mcp`	start the MCP server

Configuration

setting	default	meaning
`CONTEXTBURN_LANG` or `~/.config/contextburn/lang`	`en`	interface language: `en` or `ru`
`CONTEXTBURN_DAY_START`	`6`	hour your day starts — the daily total resets here
`CONTEXTBURN_WARN`	`30000000`	tokens/hour that turns the menu-bar counter yellow
`CONTEXTBURN_ALARM`	`90000000`	tokens/hour that turns it red

The language file exists because the menu-bar app is launched from Finder, where environment variables never reach it: echo ru > ~/.config/contextburn/lang switches both the app and the CLI.

MCP server

Let the agent read its own run efficiency mid-session. The package ships a dependency-free MCP server (stdio) with two tools: run_efficiency returns the shares as structured data, and spend_breakdown returns the full report.

claude mcp add contextburn -- uvx contextburn mcp

Or install it as a Claude Code plugin, which registers the same server:

/plugin marketplace add arsentev-ai/contextburn

/plugin install contextburn@contextburn

Editor extensions

VS Code-compatible editors (VSCodium, Cursor, Windsurf, Gitpod…) — Open VSX: arsentev-ai.contextburn. A status bar meter over the local CLI; source in editors/vscode.
Raycast — source in editors/raycast, Store submission pending.

Menu-bar app (macOS)

app/main.swift is a small status-bar app. It polls contextburn --json once a minute and shows the current burn rate with an hourly graph; click a bar to see that hour's breakdown.

swiftc -O -o ContextBurn app/main.swift

Set CONTEXTBURN_BIN=/path/to/contextburn if the CLI is not in ~/bin or the usual Homebrew paths.

Limits

Claude Code transcripts only, for now.
The cost-weighted share is only as current as the price table in bin/contextburn.

Citing

Software DOI (all versions): 10.5281/zenodo.22712985. GitHub's "Cite this repository" button gives the reference; metadata is in CITATION.cff.

Author

Evgenii Arsentev — arsentev.ai · ORCID 0000-0002-9120-7298

This project was published as tokmon on its first day and renamed to avoid confusion with unrelated tools of that name; TOKMON_* environment variables still work.

License

MIT — see LICENSE.

contextburn

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

yontu

README from the maker

Try it

Demo

Why two numbers

How it counts

Commands

Configuration

MCP server

Editor extensions

Menu-bar app (macOS)

Limits

Citing

Author

License