Prototyp · Vorschau: alle Server aus der offiziellen Registry, alle 30 Minuten synchronisiert. Bewertungen und Benutzerkonten folgen in einem späteren Schritt.
PopNx MCPMCP-Server für alle, die KI nutzen · in einfachen Worten erklärt

Skill MCP

von chrischallVersion 1.2.3i★ –iLäuft auf deinem Computer
Name in der Registryio.github.chrischall/skill-mcp

Installieren

Überblick

Beschreibung vom Entwickler (englisches Original)

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

Die drei Säulen von PopNx MCP

Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.

Was du damit machen kannst

Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.

  • Verbindung: Läuft auf deinem Computer
  • Transport: stdio
  • Kategorie: Sonstiges

Installation

Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.

Bevor du installierst

  • Basischecks: 1 von 1 bestanden
  • Läuft auf deinem Computer mit den Rechten deines Benutzerkontos (Dateien, Netzwerk, Apps).
  • Das trägst du selbst ein: SKILLS_DIR

Du brauchst

  • npmNode.js installiert (für den Befehl npx)

Welche App nutzt du?

Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.

Öffne Claude Desktop → Settings → Developer → Edit Config und füge dies in claude_desktop_config.json ein

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

Führe das in deinem Terminal aus

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

Trag die leeren Werte ein, bevor du ihn startest.

In Cursor öffnen

Oder kopier die Einstellungen selbst

In .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen

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

Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.

In VS Code öffnen

Oder kopier die Einstellungen selbst

In .vscode/mcp.json in deinem Projekt einfügen

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

Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.

Dieser Server läuft auf deinem Computer, und ChatGPT kann sich nur mit Servern im Internet verbinden. Wähle eine andere App.

Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.

Werte, die du selbst einträgst

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

Diese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.

Was er kann

Läuft auf deinem Computer; die Tool-Liste erscheint nach der Installation in deiner KI-App.

Basischecksi

Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 7. Nov. 2026

  • ✓ Bestanden

    Entwickler passt zum Repo

    Der Registry-Name wurde mit dem GitHub-Konto chrischall bestätigt, dem das Repo gehört

  • … Noch nicht geprüft

    Wird noch gepflegt

    Dieses Repo haben wir noch nicht von GitHub gelesen

  • … Noch nicht geprüft

    Hat eine Lizenz

    Dieses Repo haben wir noch nicht von GitHub gelesen

  • – Nicht zutreffend

    Endpunkt antwortet

    Dieser Server läuft auf deinem Computer; es gibt keinen Endpunkt im Internet

  • – Nicht zutreffend

    Anmeldung mit OAuth

    Läuft auf deinem Computer und nutzt stattdessen lokale Einstellungen

  • … Noch nicht geprüft

    Keine versteckten Anweisungen in Tool-Beschreibungen

    Läuft auf deinem Computer; Tool-Listen können wir nur von Endpunkten im Internet lesen

Im Vergleich mit anderen in Sonstigesi

  • Mehr Sterne als 0 % der anderen 32572 Server in dieser Kategorie
  • Neuer in der Registry veröffentlicht als 80 % der anderen 32572 Server in dieser Kategorie
  • Basischecks gleich gut wie oder besser als bei 100 % der anderen 32572 Server in dieser Kategorie

Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.

Häufige Fragen

Ist Skill MCP sicher?

Er hat 1 von 1 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.

Welche Schlüssel oder Codes braucht er?

Die Registry nennt keinen erforderlichen Schlüssel, manche Server bitten dich aber bei der ersten Nutzung, dich anzumelden.

Läuft er auf meinem Computer oder in der Cloud?

Er läuft auf deinem Computer. Deine KI-App startet ihn bei Bedarf, und die Daten laufen nicht über die Server des Entwicklers (außer der Server ruft selbst einen Onlinedienst auf).

Wird er noch gepflegt?

Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (1.2.3) kam vor 8 Tagen in die Registry.

Welche Apps können ihn nutzen?

Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du Node.js auf deinem Computer.

Was kann ich stattdessen nutzen?

In derselben Kategorie: Spec Driven Development, Remote Desktop Commander, AvaHR

Alternativen

Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.

So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti

Spec Driven Development

von formulahendry

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

Läuft auf deinem Computer★ 440MITAktualisiert vor 14 Monaten
Installieren

Remote Desktop Commander

von desktop-commander

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

Läuft in der Cloud★ 211Aktualisiert gestern
Installieren

AvaHR

von avahr.com

Read hiring data and create inactive assessment and questionnaire drafts for human review.

Läuft in der CloudAktualisiert heute
Installieren

README vom Entwickler

README öffnen

Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.

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

Nur der Anfang wird gezeigt; den Rest findest du im Repo

PopNx fragen