analyze_imageLABSCO SUMMARY
The YouTube path avoids the limit the others run into.
Video by URL or local path has to be encoded and sent inline, which puts a hard ceiling on file size; the YouTube tool hands over a link instead and sidesteps that entirely. Knowing which of the five tools applies is most of what you need to use this well. The multi-item calls are the other real capability — comparing two screenshots or picking one image out of several is a different question from describing one, and the tools are shaped for it.
What it is
An MCP server that hands images and videos to Gemini 2.0 Flash for analysis. It accepts remote URLs, local file paths and YouTube links, takes several items in one call so relationships between them can be described, and lets you steer the analysis with an optional prompt.
What you get
- One or more images analysed from URLs, with an optional prompt —
analyze_imagetakingimageUrls - The same for local image files —
analyze_image_from_pathtakingimagePaths - Videos analysed from URLs or from local paths, best suited to smaller files —
analyze_video,analyze_video_from_path - A YouTube video analysed straight from its link, with no download step and none of the size limit that applies to the other video paths —
analyze_youtube_video - Multiple items in one call, so a question about the relationship between them — which of these contains a cat, what changed between these two screenshots — is answerable
- URL validity checking, local files loaded and base64-encoded, and basic security checks on the paths it is given
Requirements
A Gemini API key, supplied as GEMINI_API_KEY. Install by cloning, npm install and npm run build, then pointing the client's command at node and dist/index.js with the key in the env block; a Smithery installer is also available. Two things to plan around: video sent by URL or path is capped by what Gemini accepts inline — around 20MB after base64 encoding — so larger files fail while YouTube analysis is unaffected; and supported video types are a specific list including video/mp4, video/mpeg, video/webm and video/3gpp, with others skipped. For the path-based tools, the assistant must give paths valid in the environment the server runs in, converting between Windows and WSL forms itself. The npm package name is image-mcp-server (1.0.0). Forked from champierre/image-mcp-server.
Setup effort
One command plus a key — npx -y @smithery/cli install @Rentapad/image-mcp-server-gemini --client claude, then supply credentials
USE CASES
01
Describing what is in a screenshot
Pass the local path with a prompt and get a description or an answer to a specific question about it.
02
Comparing several images at once
Send them in one call and ask which one contains what you are looking for, or what differs between them.
03
Summarising a video you found on YouTube
Give the link and a prompt — no download, and none of the inline size limit.
04
Checking a short clip you recorded
Analyse a small local video file directly, keeping within the inline size ceiling and the supported types.
5 tools
Listed in project docs. Your client may show a different list.
analyze_image_from_pathanalyze_videoanalyze_video_from_pathanalyze_youtube_videoBEFORE YOU INSTALL
What to know first
Tools you get
5 tools named in the project's documentation.
Requires
GEMINI_API_KEY in your environment
Where it runs
Both documented clients run the server on your machine.
INSTALLATION
Connect your client
Server setup
Build from source
Clone the repository
TERMINAL
git clone https://github.com/Rentapad/image-mcp-server-gemini.git
cd image-mcp-server-geminiInstall dependencies
TERMINAL
npm installCompile TypeScript
TERMINAL
npm run buildnpx
TERMINAL
npx -y @smithery/cli install @Rentapad/image-mcp-server-gemini --client claudeMCP Clients
Cline, Claude Desktop
JSON
{
"mcpServers": {
"image-video-analysis": {
"command": "node",
"args": [
"<YOUR_PATH_TO_IMAGE_MCP_SERVER_GEMINI>/dist/index.js"
],
"env": {
"GEMINI_API_KEY": "<YOUR_GEMINI_API_KEY>"
}
}
}
}
