MCP server for the xAI Grok API — chat, vision, search, and embeddings
Connect Grok to Claude, Cursor or any other MCP client and it stops being a tab you switch to. MCP server for the xAI Grok API — chat, vision, search, and embeddings. The grok mcp server is what makes that connection.
An MCP (Model Context Protocol) server for the xAI Grok API. Built in Rust, exposes chat completions, vision, web/X search, embeddings, and model listing as MCP tools.
The toolset is worth reading before you wire it up, because it tells you what the integration is really for:
chat — Send a chat completion request to Grok with optional multi-turn history, system prompt, structured output (JSON schema), model selection, andchat_with_vision — Analyse an image with Grok's vision capabilities given an image URL and text promptchat_with_search — Chat with Grok using live web search and/or X (Twitter) search to ground responsesembedding — Generate text embeddings using Grok's embedding modellist_models — List all available Grok models and their IDs (cached for 5 minutes)Setup follows the usual MCP pattern — install or clone the server, register it in your client's configuration file, restart the client.
Among the AI and media services options, the useful question is rarely "what can it do" but "what does it cost you to run" — permissions, credentials, and how much of your context its toolset consumes. Grok's toolset — chat, chat_with_vision, chat_with_search and 2 more — 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 |
|---|---|
| chat | Send a chat completion request to Grok with optional multi-turn history, system prompt, structured output (JSON schema), model selection, and multi-agent research |
| chat_with_vision | Analyse an image with Grok's vision capabilities given an image URL and text prompt |
| chat_with_search | Chat with Grok using live web search and/or X (Twitter) search to ground responses |
| embedding | Generate text embeddings using Grok's embedding model |
| list_models | List all available Grok models and their IDs (cached for 5 minutes) |
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.