GitHub
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
Beschreibung vom Entwickler (englisches Original)
Workstation-local event bus: agents wait on or emit CI/pytest/Docker/filesystem events, no polling.
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": {
"waitbus": {
"command": "uvx",
"args": [
"waitbus"
]
}
}
}Führe das in deinem Terminal aus
claude mcp add waitbus -- uvx waitbusIn .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"waitbus": {
"command": "uvx",
"args": [
"waitbus"
]
}
}
}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": {
"waitbus": {
"type": "stdio",
"command": "uvx",
"args": [
"waitbus"
]
}
}
}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 astrogilda 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 (0.2.0) kam vor 4 Monaten 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: GitHub, Desktop Commander, Cloudflare MCP
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
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
MCP server for terminal commands, file operations, and process management
Cloudflare MCP servers
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.
One `wait` verb that blocks on, and queries across, every local source at once. When any agent, CI job, test, or container on your machine finishes or fails, every other tool on the box hears it: your Claude Code, your Cursor, your scripts, your CI. Clients that support server notifications get a push; the rest get one blocking `waitbus wait`. No waitbus cloud, no account, no telemetry; all processing stays on your machine.
Below: a Pydantic AI agent and a LangGraph agent, two *different* frameworks running as two separate OS processes, both wait on one local waitbus bus. One fails; the peer on the *other* framework, plus a live waitbus top view, react to the single failure broadcast.
Real frameworks and real waitbus subscribe/emit; the agents' LLMs are deterministic fakes and the failure is an injected event, so the clip runs fully offline. Reproduce the claim (not just the recording): run uvx waitbus demo for the gentler single-agent walk-through (no clone, no install), or, for the exact two-framework proof shown above, clone the repo and run uv run --group agent-recipes python -m examples.hero_swarm (Linux-verified; prints PROVEN: two DIFFERENT frameworks woke on ONE peer's failure ). Higher-quality MP4 at hero.mp4 . Maintainers re-render this recording from docs/demo/.waitbus-demo/ with make hero (dev-only; needs vhs, ttyd, tmux, and JetBrains Mono).
Try it now, no install:
uvx waitbus demoboots a real local bus and returns the instant an event lands, fully offline (~8 s).
waitbus is the workstation-local, cross-harness status bus that lets the tools on one machine hear each other. It does three things: ingest events, broadcast them, and replay them.
Ingest: a blocking wait/emit primitive lets any agent or script (across Cursor, Claude Code, and any tool on the box) wait on, or emit, events from five built-in sources (GitHub Actions CI, pytest sessions, Docker container lifecycle, filesystem changes, and Prometheus Alertmanager) plus any plugin source registered under the waitbus.sources.v1 entry-point group.
Broadcast: events land in SQLite the moment they arrive, and a broadcast daemon fans each row to every connected consumer within about a millisecond on the local socket (measured; see benchmarks/BENCHMARKING.md). Your agent blocks on waitbus wait (including across sources at once with --all-of/--first-of) with zero agent-side polling and idle CPU until the thing it cares about happens, and waitbus on -- runs a command the moment it does (in the CLI process, not the daemon, via execve with no shell; event values arrive as namespaced WAITBUS_* environment variables and a $WAITBUS_EVENT_FILE, never as argv, so event content cannot inject flags or overwrite PATH). Because every agent on the box shares that one bus, it doubles as a same-machine coordination backplane: one agent emits, the others wake.
Replay: a durable replay log (since=) means a consumer that was offline catches up instead of missing the moment, and waitbus events analyze queries what the bus stored. It is the local opt-in event-broadcast model the OS already uses (D-Bus signals, inotify, journald), with the replay log and a wait predicate added on top. (GitHub Actions was the first source wired, which is why the examples lead with CI, but waitbus is not CI-only.) The dependency stack is lean: typer, msgspec, platformdirs, pydantic-settings, prometheus_client, stamina, and the mcp SDK, with no heavy TUI or crypto dependency. The daemon idles at roughly 40 MB RSS measured (p50 on the benchmark host, most of it the CPython interpreter baseline) over a SQLite event store and an AF_UNIX SOCK_STREAM broadcast bus with length-prefix framing. Runs on Linux (systemd-user) and macOS (launchd).
This is for you if…
waitbus wait --all-of ...). Nothing else expresses this.This is NOT for you if…
gh run watch. It's zero-setup, and for that single job we don't beat it by enough to justify a daemon.inotifywait/entr. They're far faster on raw filesystem latency (our own benchmark says so) and need no daemon.request()/respond() facet exists, but a dedicated message queue serves that center of gravity better.uvx waitbus demo # one command, no install needed
waitbus demo allocates a temporary state directory and boots the broadcast daemon, then runs two phases. Phase 1, the point: an agent blocks on waitbus wait (the same egress engine the real command uses) with zero polling and idle CPU; the moment a github workflow_run event lands, the wait returns and the demo prints the real measured event-to-unblock latency. Phase 2, breadth: the same primitive delivers every source. pytest_session, docker_container, and fs_change events fan out to a live subscriber. Nothing on your machine outside the temporary directory is touched.
A recorded MP4 + GIF walkthrough lives at docs/demo/.waitbus-demo/demo.mp4 and demo.gif (the tape script is demo.tape). Re-rendering is reproducible via make demo from that directory (requires VHS ≥ 0.10.0, ttyd, and ffmpeg); the Makefile enforces the VHS version floor and refuses to render against an older binary that could silently change tape semantics.
The four events the demo emits are synthesized in-process. There
is no real HTTP listener, no real pytest run, no real Docker
daemon, no real watchdog. A banner before each emit makes this
explicit, mirroring the
waitbus statsoutput. To wire
waitbus against real GitHub webhook deliveries, follow the Quick
start below.
Prove the primitive in ~10 seconds -- one foreground daemon, one event, no service install. Install the CLI and bootstrap state:
uv tool install waitbus # or: pipx install waitbus
waitbus init # one-time setup: state dirs, SQLite schema, scaffolds
Then, in two terminals, watch a blocking wait return the instant an emit lands on the bus:
# Terminal A -- run the broadcast daemon in the foreground (Ctrl-C to stop):
waitbus broadcast serve
# Terminal B -- block on the next agent event, then emit one from the same shell:
waitbus wait --source agent --match 'fields.event_type="agent_message"' --timeout 30s & sleep 1 # let the backgrounded wait attach to the bus before we emit (a
waitbus emit \ --delivery-id demo-1 --source agent --event-type agent_message \ --owner local --repo local --received-at "$(date +%s)" \ --payload-json '{"hello":"world"}' --ingest-method manual wait # the backgrounded waitbus wait prints "matched on source=agent" and exits 0
That round trip -- block, emit, unblock, with zero polling -- is the whole primitive. Everything below wires it to real sources and, optionally, runs the daemons permanently under your service manager.
waitbus install-credentials github-webhook-secret # optional: only for GitHub-CI waiting (enables the webhook listener)
waitbus install-systemd # Linux: copy + enable the 8 systemd-user units waitbus install-launchd # macOS: copy + bootstrap the 4 LaunchAgent plists waitbus read-events watch # live tail of incoming events
install-systemd is Linux-only; install-launchd is macOS-only. Each command refuses to run on the other platform and points at the right one.
Once events are flowing, block any script or agent on the next matching event with waitbus wait -- any source, any field, exit code carries the verdict. The wait side is always zero-setup; the *event* it waits for still has to be produced by something (an opt-in emitter or a source watcher), so each example below notes what must be emitting for it to return:
# pytest: wait for any session to finish.
waitbus wait --source pytest --match 'fields.event_type="pytest_session"' --timeout 10m
waitbus source docker --help)waitbus wait --source docker --match 'fields.event_type="docker_container"' --timeout 30s
waitbus source fs --help)waitbus wait --source fs --match 'fields.event_type="fs_change"' --timeout 5m
waitbus wait --sha 7f3a1b2 --timeout 5m
If you have used watchexec or entr to re-run a command when a file changes, waitbus wait is the same idea with a wider net: it blocks on a file change too, but it can also wait on a CI run, a pytest session, a container exit, or another agent's event, and hands the verdict back through the exit code. The bus underneath also fans every one of those events out to every other tool on the box.
[![waitbus architecture: webhook and in-process sources write to a SQLite event store; a broadcast daemon fans each row out to the CLI, MCP server, and Python SDK, which can replay with since=](https://raw.githubusercontent.com/astrogilda/wa
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