Gemini Image Analysis
About
Analyzes image and video content from URLs or local files using the Gemini 2.0 Flash model.
Details
- Author
- rentapad
- Categories
- Cloud Service, AI, Other, Media
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Setup
Install Gemini Image Analysis in your MCP client (Claude Desktop, Cursor, Windsurf, and others).
Repository: https://github.com/rentapad/image-mcp-server-gemini
Follow the installation instructions in the repository README, then restart your MCP client.
Analyzes image and video content from URLs or local files using the Gemini 2.0 Flash model.
- Analyzes content from one or more image/video URLs or local file paths.
- Analyzes videos directly from YouTube URLs.
- Can analyze relationships between multiple images or videos provided together.
- Supports optional text prompts to guide the analysis.
- High-precision recognition and description using the Gemini 2.0 Flash model.
- URL validity checking and local file loading with Base64 encoding.
- Basic security checks for local file paths.
- Handles various image and video MIME types (see Usage section for details).
To install Image Analysis Server for Claude Desktop automatically viaSmithery:
npx -y @smithery/cli install @Rentapad/image-mcp-server --client claude
# Clone the repository git clone https://github.com/Rentapad/image-mcp-server-gemini.git cd image-mcp-server-gemini # Install dependencies npm install # Compile TypeScript npm run build
To use this server, you need a Gemini API key. Set the following environment variable:
To use with tools like Cline, add the following settings to your MCP server configuration file:
Add the following tocline_mcp_settings.json:
{ "mcpServers": { "image-video-analysis": { // Consider renaming for clarity "command": "node", "args": ["/path/to/image-mcp-server/dist/index.js"], "env": { "GEMINI_API_KEY": "your_gemini_api_key" } } } }
Add the following toclaude_desktop_config.json:
{ "mcpServers": { "image-video-analysis": { // Consider renaming for clarity "command": "node", "args": ["/path/to/image-mcp-server/dist/index.js"], "env": { "GEMINI_API_KEY": "your_gemini_api_key" } } } }
Once the MCP server is configured, the following tools become available:
- analyze_image: Receives one or more image URLs and analyzes their content.
- Arguments:imageUrls(array of strings, required),prompt(string, optional).
- Arguments:imagePaths(array of strings, required),prompt(string, optional).
- Arguments:videoUrls(array of strings, required),prompt(string, optional).
- Arguments:videoPaths(array of strings, required),prompt(string, optional).
- Arguments:youtubeUrl(string, required),prompt(string, optional).
Please analyze this image: https://example.com/image.jpg
Analyzing multiple images from local paths and comparing them:
Analyze these images: /path/to/your/image1.png, /path/to/your/image2.jpeg. Which one contains a cat?
(The client would callanalyze_image_from_pathwithimagePaths: ["/path/to/your/image1.png", "/path/to/your/image2.jpeg"]andprompt: "Which one contains a cat?")
Analyzing a video from URL with a specific prompt:
Summarize the content of this video: https://example.com/video.mp4
(The client would callanalyze_videowithvideoUrls: ["https://example.com/video.mp4"]andprompt: "Summarize the content of this video")
What is the main topic of this YouTube video? https://www.youtube.com/watch?v=dQw4w9WgXcQ
(The client would callanalyze_youtube_videowithyoutubeUrl: "https://www.youtube.com/watch?v=dQw4w9WgXcQ"andprompt: "What is the main topic of this YouTube video?")
- Size Limit:For videos provided via URL (analyze_video) or path (analyze_video_from_path), Gemini currently has limitations on the size of video data that can be processed directly (typically around 20MB after Base64 encoding). Larger videos may fail. YouTube analysis does not have this same client-side download limit.
- Supported MIME Types:The server attempts to map and use MIME types supported by Gemini for video. Officially supported types include:video/mp4,video/mpeg,video/mov,video/avi,video/x-flv,video/mpg,video/webm,video/wmv,video/3gpp. Files with other MIME types might be skipped. YouTube videos are handled separately.
When using the..._from_pathtools, the AI assistant (client) must specifyvalid file paths in the environment where this server is running.
- If the server is running on WSL:
- If the AI assistant has a Windows path (e.g.,C:\...), it needs to convert it to a WSL path (e.g.,/mnt/c/...) before passing it to the tool.
- If the AI assistant has a WSL path, it can pass it as is.
- If the AI assistant has a WSL path (e.g.,/home/user/...), it needs to convert it to a UNC path (e.g.,\\wsl$\Distro\...) before passing it to the tool.
- If the AI assistant has a Windows path, it can pass it as is.
Path conversion is the responsibility of the AI assistant (or its execution environment).The server will try to interpret the received path as is, applying basic security checks.
When runningnpm run build, you may see an error (TS7016) about missing TypeScript type definitions for themime-typesmodule.
src/index.ts:16:23 - error TS7016: Could not find a declaration file for module 'mime-types'. ...
This is a type checking error, and since the JavaScript compilation itself succeeds, itdoes not affect the server's execution. If you want to resolve this error, install the type definition file as a development dependency.
npm install --save-dev @types/mime-types # or yarn add --dev @types/mime-types
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