Merge pull request #7418 from woladi/add-macos-vision-mcp

Add woladi/macos-vision-mcp to Multimedia Process 🤖🤖🤖
This commit is contained in:
Frank Fiegel
2026-06-23 10:07:12 -07:00
committed by GitHub
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@@ -2328,6 +2328,7 @@ Provides the ability to handle multimedia, such as audio and video editing, play
- [TopazLabs/topaz-mcp](https://github.com/TopazLabs/topaz-mcp) 📇 ☁️ 🍎 🪟 🐧 - AI image enhancement (upscaling, denoising, sharpening) via Topaz Labs API. Supports 8 models including Standard V2, Wonder 2, Bloom, and Recover 3. - [TopazLabs/topaz-mcp](https://github.com/TopazLabs/topaz-mcp) 📇 ☁️ 🍎 🪟 🐧 - AI image enhancement (upscaling, denoising, sharpening) via Topaz Labs API. Supports 8 models including Standard V2, Wonder 2, Bloom, and Recover 3.
- [verIdyia/autoeq-mcp](https://github.com/verIdyia/autoeq-mcp) [![autoeq-mcp MCP server](https://glama.ai/mcp/servers/verIdyia/autoeq-mcp/badges/score.svg)](https://glama.ai/mcp/servers/verIdyia/autoeq-mcp) 🐍 🏠 🍎 🪟 🐧 - Headphone/IEM equalization database with 8,800+ models from AutoEQ. Search by name or sound signature, get parametric EQ settings, compare headphones band-by-band, and browse Harman preference score rankings. Includes automatic sound signature classification (Neutral, Warm, Bright, Dark, V-shaped, etc.). - [verIdyia/autoeq-mcp](https://github.com/verIdyia/autoeq-mcp) [![autoeq-mcp MCP server](https://glama.ai/mcp/servers/verIdyia/autoeq-mcp/badges/score.svg)](https://glama.ai/mcp/servers/verIdyia/autoeq-mcp) 🐍 🏠 🍎 🪟 🐧 - Headphone/IEM equalization database with 8,800+ models from AutoEQ. Search by name or sound signature, get parametric EQ settings, compare headphones band-by-band, and browse Harman preference score rankings. Includes automatic sound signature classification (Neutral, Warm, Bright, Dark, V-shaped, etc.).
- [rendobar/mcp](https://github.com/rendobar/mcp) [![rendobar/mcp MCP server](https://glama.ai/mcp/servers/rendobar/mcp/badges/score.svg)](https://glama.ai/mcp/servers/rendobar/mcp) 🎖️ 📇 ☁️ - Submit media-processing jobs to the Rendobar API and upload local files in one tool call. Transcode, run raw FFmpeg, burn captions, and add watermarks over REST. Free tier. - [rendobar/mcp](https://github.com/rendobar/mcp) [![rendobar/mcp MCP server](https://glama.ai/mcp/servers/rendobar/mcp/badges/score.svg)](https://glama.ai/mcp/servers/rendobar/mcp) 🎖️ 📇 ☁️ - Submit media-processing jobs to the Rendobar API and upload local files in one tool call. Transcode, run raw FFmpeg, burn captions, and add watermarks over REST. Free tier.
- [woladi/macos-vision-mcp](https://github.com/woladi/macos-vision-mcp) [![macos-vision-mcp MCP server](https://glama.ai/mcp/servers/woladi/macos-vision-mcp/badges/score.svg)](https://glama.ai/mcp/servers/woladi/macos-vision-mcp) 📇 🏠 🍎 - Local OCR and image analysis via Apple Vision Framework. Wraps macOS's native Vision API to expose OCR for images and PDFs (with reading-order paragraphs, bounding boxes, line/paragraph IDs, and confidence), face / barcode / QR / document-corner detection, and image classification — all as MCP tools any client (Claude Code, Claude Desktop, Cursor, Codex CLI) can call. ~97% token savings vs sending raw images. Fully offline, no API keys, files never leave the Mac. One-line install: `npx -y macos-vision-mcp`.
### 🖥️ <a name="os-automation"></a>OS Automation ### 🖥️ <a name="os-automation"></a>OS Automation