Image Analysis Server
Analyzes images using the GPT-4o-mini model via the OpenAI API.
image-mcp-server
An MCP server that receives image URLs or local file paths and analyzes image content using the GPT-4o-mini model.
Features
- Receives image URLs or local file paths as input and provides detailed analysis of the image content
- High-precision image recognition and description using the GPT-4o-mini model
- Image URL validity checking
- Image loading from local files and Base64 encoding
Installation
Installing via Smithery
To install Image Analysis Server for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @champierre/image-mcp-server --client claude
Manual Installation
# Clone the repository
git clone https://github.com/champierre/image-mcp-server.git # or your forked repository
cd image-mcp-server
# Install dependencies
npm install
# Compile TypeScript
npm run build
Configuration
To use this server, you need an OpenAI API key. Set the following environment variable:
OPENAI_API_KEY=your_openai_api_key
MCP Server Configuration
To use with tools like Cline, add the following settings to your MCP server configuration file:
For Cline
Add the following to cline_mcp_settings.json
:
{
"mcpServers": {
"image-analysis": {
"command": "node",
"args": ["/path/to/image-mcp-server/dist/index.js"],
"env": {
"OPENAI_API_KEY": "your_openai_api_key"
}
}
}
}
For Claude Desktop App
Add the following to claude_desktop_config.json
:
{
"mcpServers": {
"image-analysis": {
"command": "node",
"args": ["/path/to/image-mcp-server/dist/index.js"],
"env": {
"OPENAI_API_KEY": "your_openai_api_key"
}
}
}
}
Usage
Once the MCP server is configured, the following tools become available:
analyze_image
: Receives an image URL and analyzes its content.analyze_image_from_path
: Receives a local file path and analyzes its content.
Usage Examples
Analyzing from URL:
Please analyze this image URL: https://example.com/image.jpg
Analyzing from local file path:
Please analyze this image: /path/to/your/image.jpg
Note: Specifying Local File Paths
When using the analyze_image_from_path
tool, the AI assistant (client) must specify a valid file path 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 Windows path (e.g.,
- If the server is running on Windows:
- 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.
- If the AI assistant has a WSL path (e.g.,
Path conversion is the responsibility of the AI assistant (or its execution environment). The server will try to interpret the received path as is.
Note: Type Errors During Build
When running npm run build
, you may see an error (TS7016) about missing TypeScript type definitions for the mime-types
module.
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, it does 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
Development
# Run in development mode
npm run dev
License
MIT
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