vmlx: Ultra‑Fast LLM Caching & Persistent Disk Store for Founders
From the repo · “vMLX - Use MLX models easily - JANGQ (GGUF for MLX) - Not dependant on mlx_vlm”
Use Python to quickly make super fast machine learning models.
"A founder wants to add product recommendations to their e-commerce site. They use vMLX to quickly build a fast ML model, which runs on their MCP server. They train the model with a dataset of customer purchases and product features. The model helps their site suggest relevant products to each customer."
- •When you need to deploy large machine learning models and want to reduce memory usage
- •When you require fast model serving and inference with low latency
- •When you want to survive model serving interruptions, such as restarts, with a disk cache
curl -X POST -H 'Content-Type: application/json' -d '@input.json' http://localhost:8000/predict
Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
Installs with a command or two; your AI agent can do it for you.
mkdir -p ~/.claude/skills/vmlx && curl -fsSL https://workflowstacks.com/api/skills/vmlx/claude-skill -o ~/.claude/skills/vmlx/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
What's inside — free to inspect
Read the entire source before you build — unlike paid marketplaces that hide it behind a buy button.
Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
Installs with a command or two; your AI agent can do it for you.
mkdir -p ~/.claude/skills/vmlx && curl -fsSL https://workflowstacks.com/api/skills/vmlx/claude-skill -o ~/.claude/skills/vmlx/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
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Do this with a working workflow
Pages we wrote and tested that put a skill like this to work — importable n8n templates, outcome guides and Claude Desktop configs.
AI Product Description Writer
Turn a Google Sheet of product names + features into polished, conversion-focused descriptions — in bulk.
Outcome guideAutomate your product descriptions with AI
You keep your products in a Google Sheet. The workflow reads each one, writes a benefit-led description in a consistent brand voice, and saves it back — for your whole catalog at once. You review and publish.
MCP configMemory (knowledge graph) MCP config
Persistent memory across chats via a local knowledge graph.
Related skills
More mcp-server tools founders pair with this one.