Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
제작자가 쓴 설명(영어 원문)
Check whether a CLI command name is already taken across npm, PyPI, crates.io, Go, Debian and more
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
GLOBAL_EXECUTABLES_DATASET_ROOT, GLOBAL_EXECUTABLES_CACHE_DIR, GLOBAL_EXECUTABLES_OFFLINE필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"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"
}
}
}
}터미널에서 이 명령어를 실행하세요
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 mcp실행하기 전에 빈 값을 채워 주세요.
프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"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"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"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"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
GLOBAL_EXECUTABLES_DATASET_ROOT envGLOBAL_EXECUTABLES_CACHE_DIR envGLOBAL_EXECUTABLES_OFFLINE env이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 7일 점검
레지스트리 이름이 GitHub 계정 asopitech-labs 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(1.4.1)은 18일 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Python (uv), Docker도 있어야 해요.
같은 카테고리에는: Spec Driven Development, Remote Desktop Commander, AvaHR
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
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.
Read hiring data and create inactive assessment and questionnaire drafts for human review.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
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).
앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요