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)
Check whether a CLI command name is already taken across npm, PyPI, crates.io, Go, Debian and more
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。
GLOBAL_EXECUTABLES_DATASET_ROOT, GLOBAL_EXECUTABLES_CACHE_DIR, GLOBAL_EXECUTABLES_OFFLINE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": {
"global-executables": {
"command": "uvx",
"args": [
"global-executables",
"mcp"
],
"env": {
"GLOBAL_EXECUTABLES_DATASET_ROOT": "your-value",
"GLOBAL_EXECUTABLES_CACHE_DIR": "your-value",
"GLOBAL_EXECUTABLES_OFFLINE": "your-value"
}
}
}
}在终端中运行这条命令
claude mcp add global-executables --env GLOBAL_EXECUTABLES_DATASET_ROOT=your-value --env GLOBAL_EXECUTABLES_CACHE_DIR=your-value --env GLOBAL_EXECUTABLES_OFFLINE=your-value -- uvx global-executables mcp运行前请先填写空着的值。
粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"global-executables": {
"command": "uvx",
"args": [
"global-executables",
"mcp"
],
"env": {
"GLOBAL_EXECUTABLES_DATASET_ROOT": "your-value",
"GLOBAL_EXECUTABLES_CACHE_DIR": "your-value",
"GLOBAL_EXECUTABLES_OFFLINE": "your-value"
}
}
}
}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": {
"global-executables": {
"type": "stdio",
"command": "uvx",
"args": [
"global-executables",
"mcp"
],
"env": {
"GLOBAL_EXECUTABLES_DATASET_ROOT": "your-value",
"GLOBAL_EXECUTABLES_CACHE_DIR": "your-value",
"GLOBAL_EXECUTABLES_OFFLINE": "your-value"
}
}
}
}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。
GLOBAL_EXECUTABLES_DATASET_ROOT envGLOBAL_EXECUTABLES_CACHE_DIR envGLOBAL_EXECUTABLES_OFFLINE env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 asopitech-labs 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(1.4.1)于18天前进入注册中心。
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), Docker。
同一分类中有:Spec Driven Development, Remote Desktop Commander, SuperCollider
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.
Make sound with SuperCollider: synths, drums, chords, melodies and soundscapes over OSC.
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。
Global Executables
Check whether a CLI command name is already in use—before you publish it.
Search executable names across npm, PyPI, crates.io, Go modules, Homebrew, Debian, and more from your AI agent or browser.
Try the Playground · Install the MCP server · Read the docs · Browse the data
A package name is not necessarily the command it installs. Searching registries for package names can miss a collision such as a differently named package that already ships your proposed command.
| Ordinary package search | Global Executables |
|---|---|
| Searches package and repository names | Searches the actual installed command name |
| Leaves evidence scattered across registries | Normalizes providers across ecosystems |
| A missing result can look deceptively final | Reports coverage and absence confidence |
| Requires a person to repeat the work | Lets AI agents check names in batches and verify known packages |
The index preserves the relationship that matters:
command → provider → package → ecosystem → source evidence
Open the [Index Playground](https://asopitech-labs.github.io/global-executables/) to check a name, find similar commands, inspect providers, or review source coverage. The Playground reads the same public JSON dataset as the MCP server, and query data is not sent to a third-party API.
For an AI-assisted check, connect the MCP server below and ask:
I am naming a new CLI. Check `envc`, `evcr`, `evpk`, and `envcp` for exact
collisions and confusingly similar commands. Keep rejected names internal and explain the coverage caveat for every survivor.
The agent can reject envcp with evidence instead of relying on a package-name search: the command is provided on PyPI by both chaperone and envcp.
| Capability | What it gives you |
|---|---|
| Exact and batch checks | Collision results for one name or a candidate set |
| Similar-name search | Typo and confusion candidates before you publish |
| Provider provenance | Package, ecosystem, version, source, and evidence confidence |
| Coverage-aware negatives | An explicit distinction between “not found” and “proven free” |
| Installation resolution | Conservative install and invoke steps for a target environment |
| Public, inspectable data | Versioned JSON, schemas, freshness, and coverage on GitHub |
The server has no write tools and never installs or executes the software it finds.
uvThe recommended setup uses uv. You do not need to clone this repository, download the dataset, or create an API key.
Verify that uvx is available:
uvx --version
Choose your client below. The first launch downloads the package from PyPI; later launches reuse uv's cache.
Claude Desktop and Cursor
Add this to claude_desktop_config.json, ~/.cursor/mcp.json, or a project's .cursor/mcp.json:
{
"mcpServers": { "global-executables": { "command": "uvx", "args": ["global-executables", "mcp"] } } }
Claude Code
claude mcp add global-executables -- uvx global-executables mcp
Codex CLI
codex mcp add global-executables -- uvx global-executables mcp
Start a new Codex session after adding the server. See the Codex setup tutorial for registration checks and a source-checkout setup.
VS Code
Add this to .vscode/mcp.json:
{
"servers": { "global-executables": { "type": "stdio", "command": "uvx", "args": ["global-executables", "mcp"] } } }
Docker (any stdio MCP client)
Use this server entry instead of the uvx entry:
{
"command": "docker", "args": ["run", "-i", "--rm", "ghcr.io/asopitech-labs/global-executables-mcp:latest"] }
The image is public and contains the server, but not a stale copy of the dataset.
Try one of these prompts:
Is the command name `envc` already taken? Check similar names too.
Check `envc`, `evcr`, `evpk`, and `envcp` as possible CLI names. Do not show
rejected candidates; explain the dataset coverage for the survivors.
Which package provides the `ruff` executable, and how should I install it in a
Python 3.12 project virtual environment?
The agent will normally call check_executables for a batch and search_similar_executables for the candidates that remain.
[!IMPORTANT]
found: truemeans a collision.found: falsemeans only that the current
snapshot contains no match. When
statusisunknown, partial source coverage
means the name is not proven to be available. Read
warnings,
absence.confidence, andcoverage_scopebefore adopting a name.
Snapshot lookups fetch only the public dictionary branch files a query needs, cache them in the current user's cache directory, and revalidate them with ETag. Cached files remain usable when the network is temporarily unavailable.
| Requirement | Details |
|---|---|
| Authentication | None |
| Local dataset | Not required |
| Default transport | stdio |
| Data access | On-demand HTTPS from the public dictionary branch |
| Writes or command execution | Lookup never executes software; verified discovery can reserve a Git branch only on a configured runner |
| Supported Python | 3.11+ (handled automatically by uvx) |
| Variable | Effect |
|---|---|
GLOBAL_EXECUTABLES_DATASET_ROOT | use a local checkout of the dictionary branch instead of HTTPS |
GLOBAL_EXECUTABLES_CACHE_DIR | cache location (default ~/.cache/global-executables, ~/Library/Caches/global-executables, or %LOCALAPPDATA%\global-executables\Cache) |
GLOBAL_EXECUTABLES_OFFLINE=1 | serve only cached files, never touch the network |
uvx global-executables mcp --help lists the same options as flags. The package is published to PyPI from release 1.3.0. See the MCP guide for HTTP transport, offline operation, and running from a source checkout.
| Tool | Use it when you want to… |
|---|---|
check_executable | check one exact, case-sensitive command name |
check_executables | check several naming candidates in one call (recommended) |
get_executable | retrieve providers and provenance for a known command |
search_executables | search by prefix, length, ecosystem, or scope |
search_similar_executables | find names that may be confused with a candidate |
get_coverage | inspect source coverage, freshness, and warnings |
assess_executable / assess_executables | add freshness, activity, popularity, and collision-risk signals |
resolve_installation / resolve_installations | derive environment-specific install and invoke guidance |
discover_published_package | verify commands declared by one current npm or PyPI release |
Snapshot lookup tools are read-only. discover_published_package makes bounded live registry and artifact requests without executing package code. On a designated runner configured with Git write access, successful verification also reserves an immutable intake/ branch for central revalidation. The result reports reservation.status; an unconfigured copy reports unavailable and does not claim publication. Neither MCP nor CLI writes the published dictionary directly. The repository's Verify and reserve published package discovery GitHub Actions workflow is the designated runner; it invokes both CLI and MCP before the collector. Installation resolvers return instructions; they never install or execute software. Full inputs and result contracts are documented in the MCP guide.
The scheduled intake collector validates and rechecks reserved evidence before merging it into artifact-data. The regular refresh remains the only writer of the dictionary branch. See the MCP guide for runner configuration and the reservation lifecycle.
| Family | Sources | Typical executable evidence |
|---|---|---|
| System packages | Debian, Ubuntu, Arch Linux | Installed package file lists |
| macOS packages | Homebrew | Formula metadata and package contents |
| Language registries | npm, PyPI, crates.io, Go modules, RubyGems, Packagist | Declared bins, entry points, or executable targets |
| C and C++ recipes | ConanCenter, vcpkg, xmake-repo | Built file lists, tool declarations, or marked binary packages |
Every provider keeps its source and a confidence level (direct, filesystem, or inferred). Coverage differs by ecosystem, so negative results carry explicit coverage metadata instead of pretending that every registry is exhaustive. See Data Sources for collection details and coverage and freshness for the result contract.
| If you want to… | Start here |
|---|---|
| Connect an MCP client or use HTTP transport | MCP access and agent integration |
| Configure Codex step by step | Codex MCP tutorial |
| Verify a clean source checkout | Setup and verification |
| Understand records, indexes, and schemas | Data model |
| Review collection scope and attribution | Data sources |
| Operate or contribute to the data pipeline | Operations |
The client says uvx was not found
Install uv, confirm that uvx --version works in a new terminal, and restart the MCP client so it receives the updated PATH. If the client uses a restricted environment, set the configuration's command to the absolute path reported by command -v uvx (macOS/Linux) or where uvx (Windows).
只显示了开头部分;其余内容请在仓库中阅读