GitHub
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
Beschreibung vom Entwickler (englisches Original)
Lets your AI find open-source tools on GitHub and install them as sandboxed MCP tools.
Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.
Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.
Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.
Du brauchst
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": {
"legwork": {
"command": "uvx",
"args": [
"legwork-mcp",
"hub"
]
}
}
}Führe das in deinem Terminal aus
claude mcp add legwork -- uvx legwork-mcp hubIn .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"legwork": {
"command": "uvx",
"args": [
"legwork-mcp",
"hub"
]
}
}
}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 .vscode/mcp.json in deinem Projekt einfügen
{
"servers": {
"legwork": {
"type": "stdio",
"command": "uvx",
"args": [
"legwork-mcp",
"hub"
]
}
}
}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.
Diese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.
Läuft auf deinem Computer; die Tool-Liste erscheint nach der Installation in deiner KI-App.
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
Der Registry-Name wurde mit dem GitHub-Konto kumarganduri bestätigt, dem das Repo gehört
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieser Server läuft auf deinem Computer; es gibt keinen Endpunkt im Internet
Läuft auf deinem Computer und nutzt stattdessen lokale Einstellungen
Läuft auf deinem Computer; Tool-Listen können wir nur von Endpunkten im Internet lesen
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
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.
Die Registry nennt keinen erforderlichen Schlüssel, manche Server bitten dich aber bei der ersten Nutzung, dich anzumelden.
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).
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (0.7.19) kam vor 6 Tagen in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du Python (uv) auf deinem Computer.
In derselben Kategorie: GitHub, Desktop Commander, Cloudflare MCP
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
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
MCP server for terminal commands, file operations, and process management
Cloudflare MCP servers
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.
Your AI finds the open-source tool it needs on GitHub. Legwork installs it in a sandbox.
https://github.com/user-attachments/assets/9e9b80b5-99ff-4d21-b689-74655418f23d
A real run in Claude Desktop. The 25-second install is sped up; the malware repos' names are masked.
Add Legwork to Claude, Cursor, Codex, opencode or any MCP client once. When you ask for something your AI has no tool for, it searches GitHub, picks a repo, and asks you to approve installing it. Legwork then checks the code for hidden payloads, builds a working tool for it in a sandbox, tests it, and hands it over. In your home folder it can only read the folders you allow.
claude mcp add legwork -- uvx legwork-mcp hub --allow-read ~/Downloads
Then just ask. Four to try first, all from the public cache, so they need no API key:
Saying "use Legwork" matters in Claude Desktop: without it, Claude may reach for its own cloud code sandbox, which can't see the files on your computer unless you attach them.
Your AI finds the tool (faster-whisper, rembg, pdfplumber, qrcode), you approve the install, and about a minute later it does the job. Files a tool makes are copied to ~/Legwork/outputs/. On macOS, the first time a tool reads Downloads, macOS asks whether uvx may access it; allow it once. If something doesn't work, uvx legwork-mcp doctor checks your setup. Or build one tool yourself: uvx legwork-mcp owner/repo (a model key for repos not in the cache).
On 2026-09-26 we ran Legwork against the 10 most-starred AI repos created on GitHub in the previous week, taken exactly as search ranked them, with nothing skipped for being hard:
| Outcome | Repos |
|---|---|
| ✅ Built a working MCP server | 3 — an npm CLI, a Python library, a Go binary |
| ↩️ Refused, with the right reason | 5 — two Android/macOS apps, a desktop app, a repo with no usage docs, a tool that needs its own API keys |
| 🛑 Blocked before install (malware) | 2 |
Two of those top-10 "AI tools", about 700 stars each and three days old at the time, carried the same byte-identical obfuscated dropper under different file names. Legwork's pre-install scan refused both in about a second. Nothing from them was installed or run. Stars are not a trust signal.
The tripwire has to stay quiet on ordinary code too. Run over the 150 most-starred Python, JavaScript and TypeScript repos on GitHub (2026-10-01), it blocks one: lodash, for a vendored 2009 debugging script that really does run eval(unescape(...)).
Full write-up, including what failed along the way and what we fixed: docs/designs/legwork-trending-trial-2026-09-26.md.
A second, larger run on the next 22 new trending repos, with two models: gpt-5 built 12 and refused 10 with reasons, with no crashes; OpenRouter's free Nemotron built 4. That run also caught two false malware alarms and a gap where only published packages could be installed, both fixed. Write-up.
legwork hub is one MCP server that gives your AI five tools: find_tools, install_tool, install_status, list_installed_tools and use_tool.
claude mcp add legwork -- uvx legwork-mcp hub --allow-read ~/Downloads
For Claude Desktop (macOS), download legwork.mcpb and double-click it. Desktop installs it as an extension and lets you pick the folders tools may read (Downloads by default) and whether they may use the internet, under Settings → Extensions → Legwork → Configure. It runs the released legwork-mcp from PyPI, pinned to that release.
Or, for Cursor or Claude Desktop without the extension, add this to the MCP config (for Claude Desktop, while the app is quit), with your own user name in the path: a folder that doesn't exist stops the hub from starting.
{ "mcpServers": { "legwork": { "command": "uvx",
"args": ["legwork-mcp", "hub", "--allow-read", "/Users/you/Downloads"] } } }
For opencode, add this to ~/.config/opencode/opencode.json. opencode runs MCP tools without asking by default, so the permission line is what makes it ask you before an install:
{
"$schema": "https://opencode.ai/config.json", "mcp": { "legwork": { "type": "local", "command": ["uvx", "legwork-mcp", "hub", "--allow-read", "~/Downloads"] } }, "permission": { "legwork_install_tool": "ask" } }
legwork build asks y/N in the terminal).--allow-net. Secret folders (~/.ssh, ~/.aws, ...) are refused outright.pdfplumber__extract_tables), and use_tool works in clients that don't refresh their tool list. Installs are remembered across restarts.37 tools are in the [public cache](cache/) and install in about a minute with no API key: speech-to-text, OCR, background removal, PDFs and Office files, video, YouTube transcripts, charts, DuckDB and CSV tools, maths and units, and linters and formatters. Each was built, reviewed by hand and tried with a real call before it was added, and pins the version of the package it wraps (its dependencies resolve at install). The cache a release reads is the one tagged with that release, so a change to the cache reaches you only with an upgrade. Others need a model key, and building takes 1–5 minutes. Put the key in ~/.legwork.env (three lines, chmod 600) and the hub reads it when it needs to build, so the key never goes in your MCP config, where it would sit in plain text.
legwork find "extract tables pdf" runs the same search from your terminal.
--allow-net; without it they install, then can't connect.~/Legwork/outputs/ /, and the reply says where; images also come back inline. Your granted folders stay read-only, so a tool can't write next to your files. The copies are never executable, and on macOS they get the same quarantine flag as downloads. --outputs DIR puts them elsewhere, --outputs off turns copying off.find_tools uses 2 to 4. Cached tools still show up when GitHub says no. For 30 a minute, add GITHUB_TOKEN= to ~/.legwork.env.Legwork is a standard MCP server over stdio, so any client that runs local MCP servers can use it. What differs is whether the client asks you before it calls a tool. Legwork labels its tools (searching only reads; installing acts), and the clients marked "asks" use those labels.
| Client | Tested | Add Legwork | Before an install |
|---|---|---|---|
| Claude Code | ✅ | claude mcp add legwork -- uvx legwork-mcp hub --allow-read ~/Downloads | asks |
| Claude Desktop | ✅ | JSON above | asks |
| Cursor | ✅ | JSON above | its default Auto-review mode lets an AI decide, and ran installs without asking in our test; to approve every install, set Settings → Agents → Approvals & Execution to Allowlist and leave install_tool off the list |
| opencode | ✅ 1.18 | JSON above | asks only with the permission line above |
| Codex CLI | ✅ 0.159 | codex mcp add legwork -- uvx legwork-mcp hub --allow-read ~/Downloads | asks |
| Goose | ✅ 1.52 | goose session --with-extension "uvx legwork-mcp hub --allow-read ~/Downloads" | asks with GOOSE_MODE=smart_approve; the default mode doesn't |
| OpenClaw | ✅ 2026.9 | openclaw mcp add legwork --command uvx --arg legwork-mcp --arg hub --arg --allow-read --arg ~/Downloads | its default full-permission mode doesn't ask |
| Gemini CLI, Cline, Zed, Continue, ... | not yet | the same command in the client's MCP config | check the client's settings |
In every client, the folders and network you start the hub with stay the ceiling, whether or not the client asks.
Faster starts: uvx downloads Legwork on the first run, which can be slower than some clients wait (Codex allows 10 seconds; add startup_timeout_sec = 60 under [mcp_servers.legwork] in ~/.codex/config.toml). Or install it once with uv tool install legwork-mcp and use the full path that which legwork prints, plus hub ..., as the command (desktop apps don't see your shell's PATH); uv tool upgrade legwork-mcp updates it.
You need macOS or Linux and uv. Tools in the public cache need nothing else. For any other repo you also need a model key for an OpenAI-compatible chat-completions endpoint (see Model providers). Legwork itself is free; the only cost is your own model usage, which is 1–3 calls per build.
Linux: install bubblewrap (and one step on Ubuntu 24.04+)
The Linux sandbox is bubblewrap:
sudo apt install bubblewrap python3-venv # Debian/Ubuntu
sudo dnf install bubblewrap # Fedora
Ubuntu 24.04 and later block the user namespaces bubblewrap needs, unless a program's AppArmor profile allows them. Allow them for bwrap only (this is what Ubuntu does for Chrome and
Nur der Anfang wird gezeigt; den Rest findest du im Repo