GitHub
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
作者提供的说明(英文原文)
Workstation-local event bus: agents wait on or emit CI/pytest/Docker/filesystem events, no polling.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"waitbus": {
"command": "uvx",
"args": [
"waitbus"
]
}
}
}在终端中运行这条命令
claude mcp add waitbus -- uvx waitbus粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"waitbus": {
"command": "uvx",
"args": [
"waitbus"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"waitbus": {
"type": "stdio",
"command": "uvx",
"args": [
"waitbus"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
你的选择通过 Cookie 保存在这台设备上,无需账户。
这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日
注册名称已通过 GitHub 账户 astrogilda 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于–,最新版本(0.2.0)于4个月前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Python (uv)。
同一分类中有:GitHub, Desktop Commander, Cloudflare MCP
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
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
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
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
只显示了开头部分;其余内容请在仓库中阅读