Context7
Up-to-date docs for AI agents
Beschreibung vom Entwickler (englisches Original)
OpenAI Codex usage from your local logs: tokens, API-equivalent cost and plan limits.
Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.
Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.
Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.
Du brauchst
Welche App nutzt du?
Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.
Öffne Claude Desktop → Settings → Developer → Edit Config und füge dies in claude_desktop_config.json ein
{
"mcpServers": {
"codexwatch": {
"command": "uvx",
"args": [
"codexwatch-cli",
"mcp"
]
}
}
}Führe das in deinem Terminal aus
claude mcp add codexwatch -- uvx codexwatch-cli mcpIn .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"codexwatch": {
"command": "uvx",
"args": [
"codexwatch-cli",
"mcp"
]
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
In .vscode/mcp.json in deinem Projekt einfügen
{
"servers": {
"codexwatch": {
"type": "stdio",
"command": "uvx",
"args": [
"codexwatch-cli",
"mcp"
]
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
Dieser Server läuft auf deinem Computer, und ChatGPT kann sich nur mit Servern im Internet verbinden. Wähle eine andere App.
Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.
Diese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.
Läuft auf deinem Computer; die Tool-Liste erscheint nach der Installation in deiner KI-App.
Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 6. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto psychofict bestätigt, dem das Repo gehört
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieser Server läuft auf deinem Computer; es gibt keinen Endpunkt im Internet
Läuft auf deinem Computer und nutzt stattdessen lokale Einstellungen
Läuft auf deinem Computer; Tool-Listen können wir nur von Endpunkten im Internet lesen
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
Er hat 1 von 1 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.
Die Registry nennt keinen erforderlichen Schlüssel, manche Server bitten dich aber bei der ersten Nutzung, dich anzumelden.
Er läuft auf deinem Computer. Deine KI-App startet ihn bei Bedarf, und die Daten laufen nicht über die Server des Entwicklers (außer der Server ruft selbst einen Onlinedienst auf).
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (1.0.2) kam gestern in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du Python (uv) auf deinem Computer.
In derselben Kategorie: Context7, Codebase Memory, Exa
Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.
So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti
Up-to-date docs for AI agents
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Connect AI agents to Exa for web search, content fetching, and multi-step research.
Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.
codexwatch shows where your OpenAI Codex usage goes: tokens and their API-equivalent cost per day, project, model, session and tool, your plan's 5-hour and weekly limits as they stand now, and what each percent of those limits cost you. By default it reads only the session logs Codex already writes on your machine, never opens your login, and makes no network request; fetching prices and refreshing codexhop accounts are things you ask for.
pipx install codexwatch-cli # or: pip install --user codexwatch-cli
codexwatch # the overview in your terminal codexwatch dashboard # the web dashboard
You need nothing beyond the Codex logs already on this machine, so the first command already has your numbers. On Linux, ./install.sh --tray --desktop from a clone also adds an app-menu entry, a desktop shortcut and the tray.
Codex gives each model response an id. codexwatch keys every row on it, so a forked session that copies its parent's history, a subagent, a repeated token event or the same logs synced from another machine never add tokens twice. Those are the four ways Codex usage has been overcounted, and each one has a test that reproduces it.
After every response Codex writes the plan's rate-limit reading into the session log: how full the 5-hour and weekly windows are and when they reset. codexwatch reads those, so the live figures need no network call and no login.
Because each reading follows a known response, codexwatch can set the tokens spent in a window against how far the window moved. You get an exchange rate (dollars of API usage per percent of your plan, per window and per day) and a flag on any rise your local logs do not account for, such as usage from another machine or from ChatGPT itself.
Lines are filtered on their first bytes, so tool output and reasoning text are never decoded, and a growing session is read from where the last scan stopped. On the machine it was built on, 1.85 GB of logs in 59 sessions took about 2 seconds to scan the first time (measured, 2026-11-04); later scans read only new lines.
Every bundled price was copied from OpenAI's pricing pages, with the date and the page. A model with no published price is shown as unpriced and left out of dollar totals, never counted as $0. Fast mode is priced at the Fast tier, and prompts over 272K tokens at the long-context rate.
codexwatch dashboard opens a page on 127.0.0.1. It works offline, follows your system's light or dark setting, and refreshes as you work.
The top of the page is your plan: both windows with their reset times, the burn rate over the last hour, the time the window fills at that pace, and what you have spent since it reset. The red band below compares the last 30 days of usage with what your plan costs. After that come the totals for the period you pick, a daily chart, models and projects, quota forensics, recent sessions, a weekday-by-hour map, tool calls, and how your work ran (CLI, IDE or codex exec, Standard or Fast, main sessions or subagents).
Light theme and phone
codexwatch card writes a 1200 × 630 image of your month, and the dashboard's Share card button saves it as SVG or PNG. It leads with what your plan returned. Project names stay off the card unless you pass --projects, because a project name can be a client's name.
Plan prices come from OpenAI's Codex pricing page. Enterprise and Edu have no public price, so set yours with codexwatch config set plan_price 60.
codexwatch bar -f FORMAT prints one line, or a small menu, in the shape each bar expects. It reads only new log lines, so calling it every few seconds is cheap.
| Where | How |
|---|---|
| macOS menu bar | Install SwiftBar or xbar, then copy extras/swiftbar/codexwatch.30s.sh into its plugin folder (or run ./install.sh --swiftbar). |
| Linux tray | codexwatch tray, or ./install.sh --tray to start it now and at every login (--desktop also puts a shortcut on the desktop). A ring shows the 5-hour window; the menu holds both windows, today's value and your codexhop accounts. It uses your distribution's GTK bindings (python3-gi and an AppIndicator package), even when codexwatch itself was installed with pipx. |
| waybar | "custom/codex": {"exec": "codexwatch bar -f waybar", "return-type": "json", "interval": 30} |
| tmux | set -g status-right '#(codexwatch bar -f tmux)' |
| polybar, i3blocks | -f polybar, -f i3blocks |
| Shell prompt | PS1='$(codexwatch bar -f prompt --no-scan) \$ ' |
Desktop notifications fire as a window passes 75%, 90% and 100%, once each per window. The tray sends them, or run codexwatch notify from a timer.
codexwatch mcp is an MCP server, so an agent can check your usage mid-session:
codex mcp add codexwatch -- codexwatch mcp # OpenAI Codex
claude mcp add codexwatch -- codexwatch mcp # Claude Code
Then ask "how much of my 5-hour window is left?" or "what did this week cost?". The tools are usage_summary, plan_limits, quota_forensics, sessions, daily and budget_status. The server is in the official MCP Registry as io.github.psychofict/codexwatch.
codexhop keeps several ChatGPT logins for Codex and switches between them. When it is installed, codexwatch shows every account's latest reading and the one with the most room, names the account behind each plan window in the quota report, and codexwatch limits --refresh asks codexhop for fresh readings of all of them. codexwatch itself never opens a login file; it runs codexhop for anything that needs one.
codexwatch autohop moves Codex to another of your saved accounts when the live one is nearly spent. It is for accounts that are yours, such as a personal plan and your own seat in a company workspace, never a login someone shared with you; each account keeps its own limits, and OpenAI's terms of use apply to each one. It is off until you run it, and without --apply it only says what it would do:
$ codexwatch autohop
15:41:56 stay work is at 31% of its 5-hour window and 29% weekly; below 92% / 97%, so stay
With --apply it hops when the live account reaches 92% of its 5-hour window or 97% of its week, only to an account with at least 25% of its 5-hour window free, and at most once every 20 minutes. Every number can be changed in the autohop block of config.json. extras/systemd runs it every 3 minutes, and creating a file called autohop.off in the codexwatch folder stops it.
codexwatch budget add --name "Monthly" --usd 300 --every month
codexwatch budget add --name "atlas daily" --usd 20 --every day --scope project:atlas-api codexwatch budget add --name "5h headroom" --pct 80 --window 5h codexwatch budget list
A dollar or token budget adds up API-equivalent usage over the local calendar day, week (from Monday) or month, for everything or one project or model. A percent budget watches the plan's own window. Each sends a notification at 80% of its limit (--notify-pct) and again when it is spent. codexwatch budget check exits 1 when any budget is over, for scripts and CI.
Copy or sync another machine's ~/.codex (or just its sessions folder) somewhere and add it:
codexwatch sources add ~/sync/laptop-codex --machine laptop
codexwatch machines
Responses that appear in both places are counted once, by their response id.
Every report takes -p/--period (today, 7d, 30d, week, month, year, all, 2026-10, 2026-10-31), --since and --until, filters (--project, --model, --client, --machine, --account) and --json.
| Command | What it shows |
|---|---|
codexwatch | Plan limits, totals for today, 7 days, this month and all time, a 30-day strip, top models and projects |
daily, weekly, monthly | Tokens (input, cached, output, reasoning) and API value per period; --csv |
projects, models, clients, machines, tiers, efforts, agents | The same, grouped another way |
sessions | Recent sessions with title, model, turns, tokens, value and compactions; subagents under their parent |
tools | Which tools Codex called and how often |
latency | Median and 90th-percentile turn time and time to first token, per model |
hours | A weekday-by-hour map of when you use Codex |
limits | Every plan window, burn rate, when it fills, and codexhop accounts; --refresh |
quota | Dollars per percent of each window and day, and rises the logs cannot explain |
live | A full-screen view that redraws every few seconds |
dashboard | The web dashboard on 127.0.0.1:7878 |
card | The share card; --projects, --theme light, --plan-price |
bar | One line for a status bar or prompt |
tray | The Linux tray icon |
budget | add, list, rm, check |
notify | Send any due notification once |
autohop | Move to another of your own codexhop accounts when the live one is nearly spent (dry run unless --apply) |
mcp | The MCP server |
demo | The dashboard on invented data; --terminal for the overview |
export | Every response as CSV or JSON |
prices | The price list; update pulls LiteLLM's, path shows where your overrides go |
sources | add or rm another machine's logs |
| scan | Read new log lin
Nur der Anfang wird gezeigt; den Rest findest du im Repo