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Skill MCP

de chrischallversión 1.2.3i★ –iSe ejecuta en tu computadora
Nombre en el registroio.github.chrischall/skill-mcp

Instalar

Resumen

Descripción del creador (original en inglés)

Serves a directory of Agent Skills over MCP: list, load, read files, run declared scripts

Los tres pilares de PopNx MCP

Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.

Qué puedes hacer con él

Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.

  • Conexión: Se ejecuta en tu computadora
  • Transporte: stdio
  • Categoría: Otros

Instalación

Elige la app de IA que usas y copia la configuración.

Antes de instalar

Necesitas

  • npmNode.js instalado (para el comando npx)

¿Qué app usas?

Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.

Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json

{
  "mcpServers": {
    "skill": {
      "command": "npx",
      "args": [
        "-y",
        "@chrischall/skill-mcp"
      ],
      "env": {
        "SKILLS_DIR": "your-value"
      }
    }
  }
}

Ejecuta esto en tu terminal

claude mcp add skill --env SKILLS_DIR=your-value -- npx -y @chrischall/skill-mcp

Completa los valores vacíos antes de ejecutarlo.

Abrir en Cursor

O copia la configuración tú

Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json

{
  "mcpServers": {
    "skill": {
      "command": "npx",
      "args": [
        "-y",
        "@chrischall/skill-mcp"
      ],
      "env": {
        "SKILLS_DIR": "your-value"
      }
    }
  }
}

Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.

Abrir en VS Code

O copia la configuración tú

Pégalo en .vscode/mcp.json de tu proyecto

{
  "servers": {
    "skill": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@chrischall/skill-mcp"
      ],
      "env": {
        "SKILLS_DIR": "your-value"
      }
    }
  }
}

Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.

Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.

Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.

Valores que debes completar

  • SKILLS_DIR env
    Directory of skills to serve (':'-separated for several). Defaults to the example skill bundled with this package.

Esta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.

Qué puede hacer

Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.

Revisiones básicasi

Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 7 nov 2026

  • ✓ Superada

    El creador coincide con el repo

    El nombre en el registro se verificó con la cuenta de GitHub chrischall, dueña del repo

  • … Aún sin revisar

    Sigue en mantenimiento

    Todavía no hemos leído este repo en GitHub

  • … Aún sin revisar

    Tiene licencia

    Todavía no hemos leído este repo en GitHub

  • – No aplica

    El endpoint responde

    Este se ejecuta en tu computadora; no hay endpoint en internet

  • – No aplica

    Inicio de sesión con OAuth

    Se ejecuta en tu computadora y usa ajustes locales en su lugar

  • … Aún sin revisar

    Sin instrucciones ocultas en las descripciones de herramientas

    Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet

Comparado con otros en Otrosi

  • Más estrellas que el 0% de los otros 32678 servidores de esta categoría
  • Publicado en el registro más recientemente que el 80% de los otros 32678 servidores de esta categoría
  • Revisiones básicas iguales o mejores que el 100% de los otros 32678 servidores de esta categoría

Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.

Preguntas frecuentes

¿Es seguro Skill MCP?

Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.

¿Qué claves o códigos necesita?

El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.

¿Se ejecuta en mi computadora o en la nube?

Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).

¿Sigue en mantenimiento?

El repo de GitHub cambió por última vez –, y la última versión (1.2.3) llegó al registro hace 8 días.

¿Qué apps pueden usarlo?

Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Node.js en tu computadora.

¿Qué puedo usar en su lugar?

En la misma categoría: Spec Driven Development, Remote Desktop Commander, Starreel

Alternativas

Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.

Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi

Spec Driven Development

de formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

Se ejecuta en tu computadora★ 440MITActualizado hace 14 meses
Instalar

Remote Desktop Commander

de desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

Se ejecuta en la nube★ 211Actualizado anteayer
Instalar

Starreel

de starreel

Turn a script into a finished, downloadable short-drama episode — via MCP or REST.

Se ejecuta en tu computadoraActualizado hoy
Instalar

README del creador

Abrir el README

Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.

skill-mcp

An MCP server that serves a directory of Agent Skills. Point it at skills; it lists them, hands out their instructions and their bundled files, and runs only the scripts a skill declares.

It is a generic adapter, not a curated set: the skills are content it reads, and the same build serves whatever it is pointed at.

npx @chrischall/skill-mcp                       # serves the example skill bundled here

SKILLS_DIR=~/my-skills npx @chrischall/skill-mcp

The npm package is `@chrischall/skill-mcp` (unscoped skill-mcp is taken by someone else on npm). Everything else — the repo, the binary, the registry identity io.github.chrischall/skill-mcp — is unscoped.

What a skill is

A directory holding SKILL.md: YAML frontmatter (name, description, and optionally the mcp-host: block below) followed by instructions, plus whatever files those instructions refer to. Three layouts are found under each root:

<root>/SKILL.md              # the root IS one skill

/ /SKILL.md # a directory of skills /skills/ /SKILL.md

A skill is served under its DIRECTORY name, never under the name in its own frontmatter (a frontmatter name that disagrees is reported and otherwise ignored; where the root itself is the skill, the root directory names it). That is a security rule, not a tidiness one: the owner's grant names a skill, so a bundle that could choose its own name could claim its neighbour's and be handed the neighbour's granted script and granted variables. For the same reason, two directories that really do contribute one name — only possible across two roots — have both refused and reported, rather than one of them winning by scan order.

The tools

toolargumentsreturns
skill_list—every skill found: name, description, when to use it, file count, whether it declares runnable scripts and exactly which; plus problems, so an empty list is never a mystery
skill_loadnamethe SKILL.md body verbatim, plus a manifest of the bundle's files. Referenced files are not inlined — that is what skill_file is for
skill_filename, paths[]one entry per path, in request order: text, or base64 with its media type, or that path's own error. At most 1 MiB per entry, truncated: true rather than a silent cut
skill_runname, script, args[], confirmToken{exitCode, stdout, stderr, truncated, durationMs}

skill_file takes a paths[] batch, so the files a SKILL.md points at come back in one round trip: at most 8 paths per call, 1 MiB per entry and 4 MiB per call (summed from file sizes before a byte is read, so the answer never depends on the order the paths were listed in). One bad path fails only its own entry — the rest of the batch is still served. Read the caps as bounds on this server's own heap: they cap the allocation, not only the answer, because a hosted child has a hard 256 MiB data limit and a bundle may be larger than that.

Each skill is also registered as an MCP prompt (its body is the message) and each bundled file as a resource (skill:// / ), because a client that supports those surfaces presents a skill better than a tool call does. It is a second door, never the only one: when this server runs on mcp-host and a registration narrows enabledTools, prompts/list and resources/list come back empty and the handshake stops advertising those capabilities — so the tools carry the whole experience.

Discovery reports, it never goes quiet

Anything that keeps a directory from being served comes back in skill_list's problems, with the path and the reason: no SKILL.md, frontmatter that will not parse, a name two directories both claim (both refused), a declared script that is not in the bundle, a symlink leading out of the root or out of a skill, a filename the read tools could not address. One bad skill costs itself and never the listing, and there is no third outcome where something is dropped in silence — a symlinked skill directory is served when it stays inside the root (so skills/foo -> ../shared/foo works) and reported when it does not. It is served under its *target* directory's name — skills/foo -> ../bar is the skill bar, reported as a name-mismatch so a grant is written against the right name — and a directory reached twice (a link to a skill that is also listed directly) is one skill, not a duplicate.

Problem reasons

Each entry in problems is {path, reason, detail}. detail is prose for a person; reason is the stable value to switch on.

reasonmeaning
root-unreadablea configured root could not be read at all
no-skill-mda candidate directory holds no SKILL.md
unreadable-skill-mdSKILL.md is not a regular file, or could not be read
malformed-frontmatterthe frontmatter does not parse
declarationthe mcp-host: block was refused, or carries an unknown key (named in detail); the skill's scripts are affected, its instructions are not
duplicate-nametwo directories contribute one skill name; both are refused
name-mismatchthe frontmatter name disagrees with the directory name, which wins
unusable-namethe directory's own name is not addressable, so the skill is skipped
declared-script-missinga declared script is not in the bundle
symlink-escapea symlink leads out of the root or out of a skill
unusable-patha filename the read tools could not address, left out of the manifest
file-limita skill holds more files or directories than the per-skill cap (2000 each); the manifest lists what was walked
skill-limitmore skills than MAX_SKILLS (32) were found; the rest are ignored
grantMCP_SKILL_RUN names a script the skill does not declare, so that row grants nothing
environ-unscrubbedhosted, and the exec-time environment block could not be wiped, so no script runs (see the env allowlist note below)

The set is additive. New reasons arrive without a major version bump (environ-unscrubbed is the most recent), so a client that switches on reason must treat a value it does not recognise as a generic problem and show its detail, never fail on it.

The execution fence

skill_run executes third-party code. Every rule below narrows which code runs and what it is handed; each has its own test.

  • Only a script the skill DECLARES. Not "any file under scripts/", not "anything executable". An undeclared path is refused, saying it must be declared and listing the ones that are.
  • Only inside that skill's own directory. The path is checked as a string first (plain segments; no leading /, no . or .., no backslash, no percent escape, no NUL) and then again after resolution: the real path, with symlinks followed, must still be inside the skill's real directory, and it must be a regular file. Both checks, because a string check alone misses a symlink planted inside the bundle and a resolved check alone accepts shapes that should never have been joined. The same discipline governs skill_file: a read out of a skill directory is another skill's bundle at best.
  • An argv array, never a shell string. spawn with shell: false, no interpolation, no sh -c. Arguments are passed through verbatim.
  • An interpreter from a closed set, named by the declaration — never inferred from the extension and never taken from the file's own shebang, since a file that can choose its own interpreter has already chosen its own program. v1 runs `node` and nothing else (see *What v1 cannot run*).
  • Bounded, and the call always returns. A wall-clock timeout (60 s default, per-script override, hard 300 s ceiling), 1 MiB captured per stream with truncated: true rather than a silent cut, and one skill_run at a time. On timeout the process group is signalled, which reaches the script and any child that stayed in its group. It does not reach a grandchild that detached into a group of its own, and such a grandchild also holds the stdio pipes open — so the run settles on the process exiting plus a short drain, under a hard deadline, rather than on the pipes closing. That is what guarantees the tool call returns within its budget and frees the one-at-a-time lock; it is not a guarantee that a deliberately detached grandchild is dead. Bounding *that* is the tier's job (an unprivileged uid, prlimit NPROC, and a machine that stops), not this adapter's.
  • An env allowlist. A script gets PATH, HOME, LANG, TZ, TMPDIR, MCP_DATA_DIR when the host set one, the egress proxy variables (HTTP_PROXY, HTTPS_PROXY, http_proxy, https_proxy, NO_PROXY, no_proxy, NODE_USE_ENV_PROXY) when the host set them — on mcp-host's isolated tier the network is fenced and a script without them cannot reach even an allowlisted host — and exactly the variables that script asked for and the owner granted — never this server's own environment. The fixed half mirrors mcp-host's INSTALL_ALLOWLIST (packages/runner-node/src/spawn-env.ts), for the reason that file gives: a host constant a hosted declaration cannot widen by one name. This decides what a script is handed, not what a hostile script can reach. A script runs as the same uid as this server. On Linux a same-uid process can read /proc/ /environ, so at boot the server wipes that exec-time environment block (src/scrub-environ.ts; process.env keeps every value) and that one-line read comes back empty. If a kernel or sandbox refuses that wipe, a hosted server runs no script at all — skill_run refuses and skill_list reports environ-unscrubbed — unless the owner sets MCP_SKILL_ALLOW_UNSCRUBBED=1; standalone it only warns on stderr. The values still live in the server's memory, reachable through ptrace or /proc/ /mem on a kernel at Yama ptrace_scope = 0. Real isolation between skills that do not trust each other needs the tier (a distinct uid for scripts, /proc mounted hidepid=2, or a non-dumpable server); until then, only put skills in one registration if you would give each of them every credential it holds.
  • A non-zero exit is a normal, reported outcome — exit code, stdout and stderr all come back. It is never an exception that loses the output.
  • `skill_run` asks before it runs anything. On a client that can show a confirmation prompt (Claude Code) the user is asked there, unless the server sets MCP_CONFIRM_ELICITATION=off. Otherwise the first call starts no process and returns status: "confirmation-required" with a preview of exactly what would run — the interpreter, the argv, the working directory, the timeout, and the names of the variables the script would be handed (field by field in the preview) — plus a confirmToken. Only a repeat call with the same arguments and that token runs the script, once. A token is bound to that exact run: changing the skill, script or argv is refused as DRAFT_CHANGED, and a used token as TOKEN_REUSED. See Confirmations.
The skill_run preview

The first call's preview.willRun is what the user approves, and it is the confirmToken's payload: the token is bound to it. Names only — never a value.

field
skillthe skill, by its directory name
interpreterthe declared interpreter (node)
argvthe script path followed by the arguments, exactly as they will be passed
cwdthe skill's own directory, where the script runs
timeoutMsthe wall-clock budget, after the 300 s clamp

| envNames | every variable the script will be handed, sorted — not onl

Solo se muestra el principio; lee el resto en el repo

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