MCP server that turns HTML MUP panels into interactive UI tools for LLMs.
Most AI and media services work still happens through a UI a human drives. Mup MCP server moves it into the conversation instead. MCP server that turns HTML MUP panels into interactive UI tools for LLMs.
Claude creates a full slide deck with charts, tables, and themes — all through function calls.
A MUP is an interactive UI component that lives inside an LLM chat interface.
The server publishes 5 tools. What each one is for:
Chat — Built-in, always availableSlides — Presentation editor with charts, tables, themes, reading mode, and export (demo)Markdown — Markdown workspace with annotations and document managementVoice — Speech synthesis and recognition (Jarvis mode)Progress — Task progress trackingmup-mcp-server on npm is all you need. Most clients run it directly, so configuration is a few lines and a restart.
Plenty of AI and media services servers cover similar ground. The differences that matter in practice are scope of access and how much setup stands between you and a working tool call. Mup's toolset — Chat, Slides, Markdown and 2 more — is a fair guide to whether it matches your workflow. It is maintained by Ricky610329; worth a glance at recent repository activity before you build anything load-bearing on it.
SyncDev reviews every entry in this directory against the project's own documentation before publishing, and revisits them as servers change.
| Tool | What it does |
|---|---|
| Chat | Built-in, always available |
| Slides | Presentation editor with charts, tables, themes, reading mode, and export ([demo](https://youtu.be/GKeDc1DMLH0)) |
| Markdown | Markdown workspace with annotations and document management |
| Voice | Speech synthesis and recognition (Jarvis mode) |
| Progress | Task progress tracking |
{
"mcpServers": {
"mup": {
"command": "npx",
"args": ["-y", "mup-mcp-server"]
}
}
}Add to claude_desktop_config.json, then restart Claude Desktop.
Build a programmable telecommunications stack for connecting telephony services with the Internet via a cloud-based utility.
Search built for AI, not humans — semantic web search that returns model-ready content, plus code context.
Answers, not links — delegate questions to Perplexity's search-grounded models and get cited responses back.
Give your assistant a voice — text-to-speech, voice cloning and audio tools from the ElevenLabs API.
Give your assistant a real code sandbox — isolated cloud VMs for actually running the code it writes.
The ML hub in your context window — search models, datasets, papers and run Spaces from the official server.