MCP server for Grok image generation and editing
MCP server for Grok image generation and editing. Exposed over MCP by the grok mcp server, that capability becomes something an assistant can invoke while it works, not something you go and do afterwards.
An MCP (Model Context Protocol) server for xAI's Grok image generation API. Built in Rust, exposes image generation and editing as MCP tools.
Setup follows the usual MCP pattern — install or clone the server, register it in your client's configuration file, restart the client.
Everything the assistant can do here goes through one of these:
generate_image — Generate an image from a text promptedit_image — Edit an existing image using natural language instructionslist_styles — List available image styles for use with generate_imagePlenty 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. Grok's toolset — generate_image, edit_image, list_styles — is a fair guide to whether it matches your workflow. It is maintained by codeChap; 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 |
|---|---|
| generate_image | Generate an image from a text prompt |
| edit_image | Edit an existing image using natural language instructions |
| list_styles | List available image styles for use with generate_image |
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.