Figma Context MCP
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
Beschreibung vom Entwickler (englisches Original)
On-device MCP tools for macOS: local AI, speech, vision, browser automation, system control.
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.
Der Entwickler hat in der Registry keine Installationsangaben gemacht. Sieh dir unten die README des Entwicklers an.
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 6. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto ModelPiper 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 (0.0.10-beta) kam vor 20 Tagen in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code.
In derselben Kategorie: Figma Context MCP, Claude Real Video, Figma MCP Server
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
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
Let any LLM watch a video locally — and search everything it has ever watched.
The Figma MCP server brings Figma design context directly into your AI workflow.
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.
400+ Model Context Protocol tools, all running on-device. ToolPiper is a native macOS app that turns your Mac into a local AI platform: bundled inference (llama.cpp on Metal, Apple Intelligence, speech on the Neural Engine), an OpenAI-compatible API at localhost:9998, and a built-in MCP server that exposes the whole machine to any MCP client: Claude Code, Cursor, Codex, or your own scripts.
No cloud required for local models. No Docker. No Python. No API keys. Your prompts, files and outputs stay on your Mac, and you can check what ToolPiper connects to yourself: lsof -i -P | grep ToolPiper while it runs.
This repository is the official home for ToolPiper's MCP server manifest (
server.json), the Claude Code plugin (plugins/toolpiper), and the setup guides. The ToolPiper app itself is not open source, but its privacy claims do not ask for trust: every byte of network traffic is observable on your own machine. Open-source siblings live in this org: PiperSR (ANE super-resolution model), FluidAudio, mlx-audio-swift.
Install ToolPiper, launch it once, then connect any MCP client over Streamable HTTP. Loopback connections need no auth: no token, no OAuth step.
Download the disk image from modelpiper.com/download, or install with Homebrew:
brew tap modelpiper/tap
brew trust modelpiper/tap brew install --cask toolpiper
The trust line is required once: Homebrew 6 refuses casks from taps outside its own until you trust them.
Claude Code, as a plugin (one server entry, nothing to configure by hand):
claude plugin marketplace add ModelPiper/toolpiper
claude plugin install toolpiper@modelpiper
Claude Code, as a manual server:
claude mcp add --transport http toolpiper http://127.0.0.1:9998/mcp
Codex, as a plugin:
codex plugin marketplace add ModelPiper/toolpiper
codex plugin add toolpiper@modelpiper
Or as a manual server: codex mcp add toolpiper --url http://127.0.0.1:9998/mcp. Codex signs in to ToolPiper once; approve ToolPiper's consent page when it appears.
Any other MCP client, in its server configuration:
{
"mcpServers": { "toolpiper": { "type": "http", "url": "http://127.0.0.1:9998/mcp" } } }
Claude Desktop, as a one-click extension: download toolpiper-1.0.0.mcpb from Releases and double-click it; Claude Desktop shows its install sheet. The JSON block above does not apply to Claude Desktop, whose config file runs local stdio servers only. Source, build script and privacy statement: desktop-extension/. It is a small Node.js forwarder that relays Claude Desktop's stdio to the same loopback server, and it serves the directory profile: the catalog minus every tool that uses an AI model to generate images, video or audio.
Installing with an AI agent? Point it at llms-install.md.
400+ tools, 5 resources, and 5 workflow prompts. Names follow _ (vision_ocr, system_window_snap, browser_assert). The live catalog, with per-tool documentation, is at modelpiper.com/mcp-tools.
| Category | Examples | What it covers |
|---|---|---|
| Core AI | chat, audio_transcribe, audio_speak, text_embed | Local LLM inference, speech-to-text and text-to-speech on the Neural Engine, embeddings |
| Apple frameworks + RAG | vision_ocr, image_analyze, text_analyze, rag_query | Apple Vision OCR, image analysis, natural-language analysis, hybrid HNSW + BM25 document search |
| Browser automation | browser_snapshot, browser_action, browser_assert, browser_intercept | Chrome via CDP: AX-tree snapshots, self-healing selectors, network mocking, Web Vitals, coverage |
| Testing | test_run, test_save, test_export | Saved browser test sessions, fast replay, Playwright/Cypress export |
| System actions | system_* | Windows, Spaces, clipboard (with OCR'd history), audio, displays, Finder, Calendar, Reminders, Contacts, notifications, processes, network, Bluetooth, Shortcuts, and more |
| Video creator | video_record, video_render, video_edit_timeline | Screen-recorded screenplays, non-destructive timeline editing, OTIO/FCP XML/EDL export |
| Outreach | hn_search, reddit_search, github_compare, gsc_analytics | HN, Reddit, GitHub, Google Search Console |
| Model management | model_search, model_download, model_load | Search HuggingFace, download GGUF/CoreML, load/unload |
| Routing + integrations | endpoint_set, endpoint_recommend, claude_code_install | Switch inference endpoints per session, Claude Code helper install |
Resources: toolpiper://status, toolpiper://models, toolpiper://backends, toolpiper://tests, toolpiper://categories Prompts: setup-model, audit-page, create-test, voice-over, research-topic
Don't want the whole catalog in context? Pass category or profile as a query parameter on the /mcp URL. Both the tool list and the server instructions trim to match:
# Just LLM inference (core category)
claude mcp add --transport http toolpiper "http://127.0.0.1:9998/mcp?category=core"
claude mcp add --transport http toolpiper "http://127.0.0.1:9998/mcp?profile=automation"
| Transport | Endpoint | Auth |
|---|---|---|
| Streamable HTTP | POST http://127.0.0.1:9998/mcp (plus GET /mcp, the SSE channel for tools/list_changed) | None for loopback peers, enforced at the kernel socket, so Host/Origin spoofing cannot widen it. LAN and remote peers present Authorization: Bearer. |
Streamable HTTP is the only transport. ToolPiper has no stdio server, and older guides that described one are obsolete.
Your prompts, files and outputs stay on your Mac when you use local models. ToolPiper contacts our servers for update checks, a license check when you're signed in and a daily activity count, and it can send optional usage counts. You can turn the last two off in Settings, and none of them include your content. There are no crash uploads, and local use needs no account. Everything else is traffic you ask for: model downloads from HuggingFace, a cloud provider you add, and tools that explicitly target the web. You can watch it yourself:
lsof -i -P | grep ToolPiper
You will see update, license and activity requests to modelpiper.com hosts, optional usage counts to PostHog if you leave them on, plus any downloads or providers you chose, and none of them carry your content. Full policy: modelpiper.com/privacy.
Is this the same as "ToolPipe"? No. ToolPiper (this page, modelpiper.com) is the macOS MCP server by ModelPiper. Unrelated projects with similar names exist in some directories.
What does the MIT license in this repo cover? The contents of this repository: the server manifest, the Claude Code plugin, and the setup guides. The ToolPiper app itself is proprietary.
Does it work without an internet connection? Yes. Inference, speech, vision, RAG, and system tools are all on-device. You only need the network to download models.
Can other machines connect? Loopback is zero-config. LAN and remote access go through bearer-token auth.
I already added ToolPiper with `claude mcp add`. Do I need the plugin? No. Claude Code keeps your manual toolpiper server and skips the plugin's copy while the manual one exists, so nothing doubles up. The plugin is for a fresh setup, or if you remove the manual entry.