300+ on-device MCP tools for macOS — local AI, voice, vision, browser automation, system control.
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Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"io-github-modelpiper-toolpiper": {
"command": "<see-readme>",
"args": []
}
}
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300+ on-device MCP tools for macOS — local AI, voice, vision, browser automation, system control.
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300+ 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, voice 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, Windsurf, or your own scripts.
No cloud. No Docker. No Python. No API keys. Nothing leaves your Mac, and you can verify that yourself: lsof -i -P | grep ToolPiper while it runs.
This repository is the official home for ToolPiper's MCP server manifest, setup guides, and recipes. The ToolPiper app itself is not open source — but its privacy claims don't 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 from modelpiper.com, launch it once, then connect any MCP client.
Streamable HTTP (zero config — loopback connections need no auth):
claude mcp add --transport http toolpiper http://127.0.0.1:9998/mcp
{
"mcpServers": {
"toolpiper": { "type": "http", "url": "http://127.0.0.1:9998/mcp" }
}
}
stdio (the ~/.toolpiper/mcp symlink is created automatically on launch):
claude mcp add toolpiper -- ~/.toolpiper/mcp
{
"mcpServers": {
"toolpiper": { "type": "stdio", "command": "/Users/<you>/.toolpiper/mcp" }
}
}
300+ tools, 5 resources, and 5 workflow prompts. Names follow <category>_<action> (vision_ocr, system_window_snap, browser_assert). The full catalog ships names-only on the wire (~24 KB), so it fits under Claude Code's per-server payload cap without trimming.
| 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, 11 vision endpoints, 6 NLP endpoints, 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, ~10–50 ms/step replay, Playwright/Cypress export |
| System actions | system_* — ~140 tools across 26 macOS domains | 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-mo