Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
作者提供的说明(英文原文)
Evidence-backed Linux performance triage over MCP
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。
你用的是哪个应用?
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链接指向作者自己的文件;我们不托管也不重新打包它。打开文件后,Claude Desktop 会进行安装。
在终端中运行这条命令
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。
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 guillem 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(0.5.1)于2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 MCPB。
同一分类中有:Spec Driven Development, Remote Desktop Commander, SwarmMemo
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
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Talk with agent swarms: rooms, private messages and paid tasks for AI agents
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。
Stallhunt is a Linux-first command-line performance triage tool.
Repository: https://github.com/guillem/stallhunt
Traditional tools such as top, htop, iotop, vmstat, and iostat expose measurements. They are excellent tools, but the human operator still has to answer the harder question:
What is actually constraining useful work right now, who is suffering, and who is probably responsible?
Stallhunt aims to automate that reasoning.
Requirements:
/proc/pressure are required for pressure verdicts,See docs/install.md for cargo install, release tarballs, and the support matrix.
From a clone:
cargo install --path .
stallhunt
Bare stallhunt runs a default 10-second hunt. On a terminal it renders a compact, color-coded report; piped or redirected output (stallhunt | cat, >file, CI) is unchanged plain text. Use --json for the full structured evidence, --verbose to expand the compact report's collapsed caveats back to full text, or --no-color (also NO_COLOR=1) to disable color without changing the layout:
stallhunt --json
stallhunt hunt --duration 30s stallhunt hunt --verbose
Capture and replay a normalized observation:
stallhunt record --duration 10s --output incident.json
stallhunt replay incident.json stallhunt redact incident.json --output incident.redacted.json
Follow finding lifecycle for a bounded number of rolling windows. On a terminal this opens a full-screen TUI (q quit, arrows/jk select, Enter/Space show or hide detail, PageUp/PageDown/Home/End scroll, h/? help). At 120×30 or larger it also shows the selected host/cgroup's six process-role lists beside the lifecycle panels; piped output or --json remain append-only text/JSON and carry the same scoped roles:
stallhunt watch --interval 2s --count 3
Serve Model Context Protocol tools over stdio so coding agents can query diagnoses directly — a resident sampler keeps a rolling view of recent pressure for instant answers (for Claude Code: claude mcp add stallhunt -- stallhunt mcp; see docs/mcp-server.md):
stallhunt mcp [--interval 2s] [--no-sampler]
Source packaging for an OpenAI local plugin, a Linux MCPB extension for compatible clients, and official MCP Registry metadata lives in the repository. These packages deliberately keep diagnosis local instead of hosting Stallhunt on a machine other than the one being investigated. See docs/directory-distribution.md.
Generate shell completions:
stallhunt completions bash > ~/.local/share/bash-completion/completions/stallhunt
stallhunt completions zsh > ~/.local/share/zsh/site-functions/_stallhunt
Recording output paths are not overwritten unless --force is supplied. Ten-second hunts are the normal diagnostic path; sub-second observations are telemetry smoke tests and do not receive healthy or pressure verdicts. See docs/development.md for validation and opt-in acceptance commands.
The primary abstraction is lost time, not utilization.
High utilization is not automatically a problem. A machine using 95% of its RAM may be perfectly healthy. A CPU at 70% utilization may still have latency-sensitive work suffering from scheduler contention. The project therefore focuses on evidence of stalled progress:
Example output shape:
$ stallhunt
SYSTEM HEALTH: DEGRADED
Evidence: CPU PSI some avg10: 23.4% run queue latency estimate: elevated rustc CPU consumption: 735% postgres runnable delay: 3.8s / 10s
Memory: no significant pressure detected. High memory occupancy alone is not treated as a bottleneck.
This output is aspirational; the project will reach it incrementally.
The first useful release targets Linux and focuses on:
Later releases may add:
.
├── AGENTS.md ├── CHANGELOG.md ├── Cargo.toml ├── LICENSE-APACHE ├── LICENSE-MIT ├── README.md ├── src/ │ ├── analysis.rs │ ├── cgroup.rs │ ├── cli.rs │ ├── cpu.rs │ ├── duration_us.rs │ ├── io.rs │ ├── main.rs │ ├── mcp/ │ ├── memory.rs │ ├── observe.rs │ ├── psi.rs │ ├── record.rs │ ├── render.rs │ ├── report.rs │ ├── style.rs │ ├── tui/ │ └── watch.rs ├── tests/ │ ├── cgroup_acceptance.rs │ ├── cli.rs │ ├── cpu_acceptance.rs │ ├── io_acceptance.rs │ ├── mcp.rs │ ├── memory_acceptance.rs │ └── fixtures/ │ ├── cpu/ │ └── proc-* └── docs/ ├── README.md ├── install.md ├── product.md ├── architecture.md ├── data-model.md ├── telemetry.md ├── inference-engine.md ├── cli-ux.md ├── security-privileges.md ├── testing.md ├── development.md ├── codex-workflow.md ├── experiments.md ├── references.md ├── roadmap.md ├── status.md ├── glossary.md └── decisions/
Start with AGENTS.md, then docs/README.md.
Stallhunt reads bounded local Linux telemetry and does not independently send it over the network. MCP clients may transmit tool results according to their own data policies. See the full Stallhunt privacy policy for the data, storage, sharing, retention, and contact disclosures.
Dual-licensed under MIT or Apache-2.0, at your option.
For the current milestone, implemented capabilities, validation, known limits, and the next recommended task, see docs/status.md. Planned sequencing remains in docs/roadmap.md.