Generate images using gemini
Most AI and media services work still happens through a UI a human drives. Gemini Image Generation MCP server moves it into the conversation instead. Generate images using gemini.
This is a Model Context Protocol (MCP) server that provides image generation capabilities using Google's Gemini 2 API.
@modelcontextprotocol/inspector on npm is all you need. Most clients run it directly, so configuration is a few lines and a restart.
The server publishes 1 tool. What each one is for:
generateImage — Generates images using Gemini 2's experimental image generation APIConfiguration is passed through the environment: GEMINI_API_KEY. Treat anything key-shaped as a real credential — scope it to the minimum the server needs, and rotate it if it ever lands in a shared config.
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. Gemini Image Generation's toolset — generateImage — is a fair guide to whether it matches your workflow. It is maintained by sanxfxteam; 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 |
|---|---|
| generateImage | Generates images using Gemini 2's experimental image generation API. |
{
"mcpServers": {
"gemini-imagen": {
"command": "npx",
"args": ["-y", "github:sanxfxteam/gemini-mcp-server"],
"env": {
"GEMINI_API_KEY": "your_api_key_here"
}
}
}
}Configuration as documented by the project. Restart the client after saving.
| Variable | Description | Required |
|---|---|---|
| GEMINI_API_KEY | Credential the server authenticates with. | Yes |
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.
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The ML hub in your context window — search models, datasets, papers and run Spaces from the official server.