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[](https://mseep.ai/app/drumnation-unsplash-smart-mcp-server)
# 🖼️ Unsplash Smart MCP Server
> **Empower your AI agents with stunning visuals, zero hassle.**
A powerful FastMCP server that enables AI agents to seamlessly search, recommend, and deliver professional stock photos from Unsplash with intelligent context awareness and automated attribution management.
[](https://smithery.ai/server/@drumnation/unsplash-smart-mcp-server)
[](https://www.npmjs.com/package/@drumnation/unsplash-smart-mcp-server)
## 🚀 Why Choose This Unsplash Integration
In the landscape of visual content integration, our Unsplash Smart MCP Server stands out as the **definitive solution** for AI-powered image acquisition:
- **🧠 AI-Agent Optimized**: Purpose-built for AI agents like Claude in Cursor, streamlining image requests with natural language
- **🔍 Context-Aware Image Selection**: Interprets vague requests intelligently, delivering relevant images even from abstract prompts
- **⚡ Single Tool Efficiency**: Eliminates tool spam with a unified `stock_photo` tool that handles the entire image workflow
- **📊 Resource Optimization**: URL-first approach conserves bandwidth and storage while maintaining flexibility
- **✅ Automatic Attribution**: Built-in compliance with Unsplash's Terms of Service with zero developer effort
- **📁 Project-Aware Organization**: Intelligently organizes images based on your project structure (Next.js, React, Vue, etc.)
- **🧩 Seamless Integration**: Designed for minimal setup and maximum compatibility with your existing workflow
## ✨ Features Beyond Comparison
### For AI Agent Developers
- **Smart Contextual Search**: Find the perfect image through natural language requests
- **Automatic Subject Selection**: AI determines optimal image subjects from your purpose description
- **Intent-Driven Results**: Get images that match not just keywords, but the underlying intent
- **Seamless Agent Integration**: Works out-of-the-box with Claude in Cursor and other MCP-compatible agents
### For Project Efficiency
- **Two-Step Workflow**: Get URLs for controlled downloads, avoiding permission issues and unnecessary storage
- **Project-Aware File Management**: Auto-organizes images based on framework conventions
- **Intelligent Directory Creation**: Creates appropriate folder structures based on your project type
- **Progressive Enhancement**: Works with any project size, from quick prototypes to enterprise applications
### For Compliance Peace of Mind
- **Complete Attribution Management**:
- Local attribution database tracks all image usage
- Automatic embedding of photographer metadata in images (EXIF, IPTC, XMP)
- One-click generation of attribution pages in multiple formats
- Comprehensive API for attribution data
## 🛠️ Installation
### Prerequisites
- Node.js 18.x or higher
- An Unsplash API access key ([get one here](https://unsplash.com/developers))
### Local Installation (Recommended)
1. Clone the repository:
```bash
git clone https://github.com/drumnation/unsplash-smart-mcp-server.git
cd unsplash-smart-mcp-server
```
2. Install dependencies:
```bash
npm install
```
3. Configure your Cursor MCP settings:
- macOS: Edit `~/.cursor/mcp.json`
- Windows: Edit `%USERPROFILE%\.cursor\mcp.json`
- Linux: Edit `~/.cursor/mcp.json`
4. Add the following configuration:
```json
{
"servers": {
"unsplash": {
"command": "npx",
"args": ["tsx", "src/server.ts"],
"cwd": "/absolute/path/to/unsplash-smart-mcp-server",
"env": {
"UNSPLASH_ACCESS_KEY": "your_api_key_here"
}
}
}
}
```
5. Replace:
- `/absolute/path/to/unsplash-smart-mcp-server` with the actual path where you cloned the repo
- `your_api_key_here` with your Unsplash API key
6. Save the file and restart Cursor.
> **Important:** Unlike many MCP servers, this server requires direct process piping and cannot be accessed via TCP ports or through npm directly due to how it handles FastMCP's I/O interactions. The local installation method is the most reliable approach.
### Cursor CLI Alternative
If you prefer using Cursor's CLI:
```bash
claude mcp add unsplash npx tsx /path/to/unsplash-smart-mcp-server/src/server.ts --cwd /path/to/unsplash-smart-mcp-server
claude mcp config set unsplash UNSPLASH_ACCESS_KEY=your_api_key_here
```
Replace the paths and API key with your actual values.
### Via Docker (Most Reliable Method)
1. Clone the repository:
```bash
git clone https://github.com/drumnation/unsplash-smart-mcp-server.git
cd unsplash-smart-mcp-server
```
2. Create a `docker-compose.yml` file:
```yaml
services:
unsplash-mcp:
build: .
image: unsplash-mcp-server
restart: always
stdin_open: true
tty: true
environment:
- UNSPLASH_ACCESS_KEY=your_api_key_here
```
3. Build and start the container:
```bash
docker-compose up -d
```
4. Configure your Cursor MCP settings:
- macOS: Edit `~/.cursor/mcp.json`
- Windows: Edit `%USERPROFILE%\.cursor\mcp.json`
- Linux: Edit `~/.cursor/mcp.json`
5. Add the following configuration:
```json
{
"servers": {
"unsplash": {
"command": "docker",
"args": ["exec", "-i", "unsplash-mcp-unsplash-mcp-1", "tsx", "src/server.ts"],
"env": {}
}
}
}
```
6. Save the file and restart Cursor.
This setup will:
- Start the server automatically when Docker starts
- Restart the server if it crashes
- Run in the background without terminal windows
- Provide a reliable connection to Cursor
### Via Smithery (Cloud Deployment)
If you prefer cloud deployment, you can use Smithery:
1. Install the server in Cursor via Smithery:
```bash
npx @smithery/cli install @drumnation/unsplash-smart-mcp-server --client cursor --key your_api_key_here
```
2. Alternatively, you can log in to [Smithery.ai](https://smithery.ai) and deploy it through their web interface.
> **Note for Windows users:** Smithery deployment includes special handling for Windows compatibility.
For detailed instructions and troubleshooting, see the [Smithery Deployment Guide](./docs/smithery-deployment.md).
## 🧩 Integration with AI Agents
### Step-by-Step Guide for Claude in Cursor
Our Unsplash Smart MCP Server is designed to make image acquisition through AI agents effortless and intuitive:
1. **Initiate a request**: Simply ask Claude for an image in natural language
2. **AI interpretation**: Claude understands your needs and calls the `stock_photo` tool with optimized parameters
3. **Smart image selection**: The server interprets context and finds the most relevant images
4. **Presentation of options**: Claude presents you with the best matches and download commands
5. **Seamless download**: Execute the suggested commands to place images exactly where you need them
6. **Automatic attribution**: All attribution data is stored and can be accessed whenever needed
This process eliminates the traditional workflow of:
1. ~~Searching Unsplash manually~~
2. ~~Scrolling through hundreds of results~~
3. ~~Downloading images to random locations~~
4. ~~Moving files to the correct project folders~~
5. ~~Manually tracking attribution data~~
6. ~~Creating attribution pages~~
### Example Prompts for AI Agents
Ask Claude in Cursor for images using natural language prompts like these:
```
"Find a professional image for a tech startup landing page hero section"
```
## 🪟 Windows Compatibility
If you're using Windows and experiencing the "Client closed" error when running the MCP server in Cursor, follow these special configuration steps:
### Windows-specific MCP Configuration
Create a file named `mcp.json` in your `.cursor` directory (typically at `%USERPROFILE%\.cursor\mcp.json`) with one of these configurations:
#### Option 1: Direct Node Execution (Recommended)
```json
{
"mcpServers": {
"stock_photo": {
"command": "node",
"args": ["./node_modules/.bin/tsx", "path/to/unsplash-mcp/src/server.ts"],
"disabled": false,
"env": {
"UNSPLASH_ACCESS_KEY": "your_api_key_here"
},
"shell": false
}
}
}
```
#### Option 2: PowerShell Approach
```json
{
"mcpServers": {
"stock_photo": {
"command": "powershell",
"args": ["-Command", "npx tsx path/to/unsplash-mcp/src/server.ts"],
"disabled": false,
"env": {
"UNSPLASH_ACCESS_KEY": "your_api_key_here"
}
}
}
}
```
For complete documentation on Windows compatibility, see [Windows Compatibility Guide](./docs/windows-compatibility.md).
## 🛠️ API Reference
### URL-First Approach: The Smart Choice
Our architecture uses a URL-first approach rather than direct image embedding for several critical reasons:
1. **Storage Efficiency**: Prevents AI agents from unnecessarily storing large binary data in their context
2. **Bandwidth Conservation**: Reduces data transfer between services, improving response times
3. **Placement Flexibility**: Allows developers to download images exactly where they're needed
4. **Permission Management**: Avoids filesystem permission issues in restricted environments
5. **Workflow Integration**: Seamlessly integrates with existing development pipelines
This strategy enables AI agents to intelligently suggest the optimal download location based on project context, without being constrained by their own environment limitations.
### Minimizing Tool Spam and API Calls
Unlike other solutions that require multiple tool calls for searching, filtering, downloading, and attributing images, our server:
- **Unifies the entire image workflow** into a single `stock_photo` tool
- **Optimizes result retrieval** by requesting more images upfront to enable better filtering
- **Eliminates ping-pong interactions** between the agent and services
- **Reduces agent token usage** by streamlining request and response formats
This design significantly reduces the number of API calls and tool invocations, leading to faster results and lower operational costs.
## 🔄 Automatic Attribution and Compliance
### Unsplash Terms of Service: Effortless Compliance
Using images from Unsplash requires adherence to their [Terms of Service](https://unsplash.com/license). Our server handles this automatically:
1. **Attribution Data Capture**: Every image download automatically stores photographer information
2. **Metadata Embedding**: Photographer details are embedded directly into image files
3. **Attribution Database**: A local database maintains a record of all image usage
4. **Attribution Generators**: Built-in tools create HTML and React attribution components
5. **API Access**: Simple endpoints to retrieve attribution data for any project
By using our Unsplash Smart MCP Server, you are automatically compliant with Unsplash's requirements without any additional effort.
### Attribution Management System
The server includes a comprehensive attribution management system:
```javascript
// Retrieve attribution data for your project
const attributions = await fetch('http://localhost:3000/api/unsplash', {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({
method: 'get_attributions',
params: {
format: 'json', // Options: json, html, react
projectPath: '/path/to/your/project'
}
})
}).then(res => res.json());
// attributions contains complete data about every image used
```
The API can generate three types of attribution files:
1. **JSON**: Structured data for custom implementations
2. **HTML**: Ready-to-use HTML page for website footer or credits section
3. **React**: Drop-in React component for modern web applications
## 💼 Developer Workflow Integration
### Real-World Use Cases
Our Unsplash Smart MCP Server seamlessly integrates into your development workflow:
#### UI Development
- Instantly populate mockups with relevant placeholder images
- Maintain consistent image dimensions across components
- Organize images logically within your project structure
#### Documentation
- Enhance technical documentation with explanatory visuals
- Create visually appealing tutorials and guides
- Maintain proper attribution for all visual assets
#### Content Creation
- Quickly find images for blog posts and articles
- Generate visuals for social media content
- Access consistent imagery for product marketing
#### Application Development
- Populate e-commerce sites with product imagery
- Create visually rich user experiences
- Maintain separate image collections for different sections
### Framework-Specific Organization
Images are automatically organized based on your project type:
| Framework | Default Image Path | Alternate Paths |
|-----------|-------------------|----------------|
| Next.js | `/public/images/` | `/public/assets/images/` |
| React | `/src/assets/images/` | `/assets/images/` |
| Vue | `/src/assets/images/` | `/public/images/` |
| Angular | `/src/assets/images/` | `/assets/images/` |
| Generic | `/assets/images/` | `~/Downloads/stock-photos/` |
## 🥇 Competitive Differentiation
### Why Choose Our Unsplash Integration?
| Feature | Unsplash Smart MCP Server | Alternatives |
|---------|--------------|--------------|
| **AI Agent Integration** | ✅ Purpose-built for AI agent workflow | ❌ Typically requires manual parameter setting |
| **Context Awareness** | ✅ Interprets vague requests intelligently | ❌ Relies on exact keyword matching |
| **Tool Efficiency** | ✅ Single tool handles entire workflow | ❌ Often requires multiple separate tools |
| **Attribution Management** | ✅ Comprehensive system with multiple formats | ❌ Manual tracking or basic text output |
| **Project Organization** | ✅ Framework-aware folder structures | ❌ Generic downloads to a single location |
| **Installation Complexity** | ✅ Simple one-line command | ❌ Often requires multiple configuration steps |
| **Response Format** | ✅ AI-optimized with relevant context | ❌ Generic JSON requiring further processing |
| **Download Flexibility** | ✅ URL-first with intelligent suggestions | ❌ Either direct downloads or just URLs |
## ⚙️ Configuration
### Environment Variables
| Variable | Description | Default |
|----------|-------------|---------|
| `UNSPLASH_ACCESS_KEY` | Your Unsplash API access key | - |
| `PORT` | Port for the server to listen on | `3000` |
| `HOST` | Host for the server | `localhost` |
| `ATTRIBUTION_DB_PATH` | Path to store attribution database | `~/.unsplash-mcp` |
### Tool Parameters
#### stock_photo
| Parameter | Type | Description | Default |
|-----------|------|-------------|---------|
| `query` | string | What to search for (AI will choose if not specified) | - |
| `purpose` | string | Where the image will be used (e.g., hero, background) | - |
| `count` | number | Number of images to return | `1` |
| `orientation` | string | Preferred orientation (any, landscape, portrait, square) | `any` |
| `width` | number | Target width in pixels | - |
| `height` | number | Target height in pixels | - |
| `minWidth` | number | Minimum width for filtering results | - |
| `minHeight` | number | Minimum height for filtering results | - |
| `outputDir` | string | Directory to save photos | `~/Downloads/stock-photos` |
| `projectType` | string | Project type for folder structure (next, react, vue, angular) | - |
| `category` | string | Category for organizing images (e.g., heroes, backgrounds) | - |
| `downloadMode` | string | Whether to download images or return URLs | `urls_only` |
#### get_attributions
| Parameter | Type | Description | Default |
|-----------|------|-------------|---------|
| `format` | string | Output format (json, html, react) | `json` |
| `projectPath` | string | Filter attributions to a specific project path | - |
| `outputPath` | string | Where to save attribution files | - |
## 🔧 Troubleshooting
### Common Issues and Solutions
| Issue | Solution |
|-------|----------|
| **Connection Refused** | Ensure the server is running on the configured port |
| **Authentication Error** | Verify your Unsplash API key is correctly set |
| **No Images Found** | Try broader search terms or check your search query |
| **Download Permission Issues** | Use `downloadMode: 'urls_only'` and manual download commands |
| **Docker Container Exits Prematurely** | Ensure you're using `CMD ["npm", "start"]` in your Dockerfile instead of directly running the TypeScript file with tsx. This ensures the server stays running in a Docker environment. |
| **Timeout Errors** | The default MCP timeout is 60 seconds, which may be insufficient for downloading larger images or processing multiple images. For image-heavy operations: 1) Process fewer images per request, 2) Use smaller image dimensions, 3) Consider using `urls_only` mode instead of auto-download, 4) Check network connectivity |
| **Attribution Not Found** | Verify the image was downloaded through the MCP server |
| **Unhandled MCP Errors** | If you see `"McpError: MCP error -32001: Request timed out"` errors, your request is likely taking too long. Break it into smaller operations or use the URLs-only approach |
## 🤝 Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
### Development Workflow
1. Clone the repository
2. Install dependencies with `npm install`
3. Create a `.env` file with your Unsplash API key
4. Run in development mode with `npm run dev`
5. Run tests with `npm test`
## 🗺️ Roadmap
Here's what we're planning for future releases:
- **Image Editing Capabilities**: Basic resizing, cropping, and adjustment tools
- **Advanced Search Filters**: More granular control over image selection
- **Batch Processing**: Handle multiple image requests efficiently
- **Custom Collections**: Save and manage groups of images for projects
- **Team Collaboration**: Share attribution and image collections
- **Usage Analytics**: Track image usage across projects
- **Additional Image Sources**: Integration with other stock photo providers
- **Improved Timeout Handling**: Enhanced timeout configuration and recovery mechanisms
## 📄 License
MIT License
## 📚 Attribution Requirements
When using images from Unsplash, you must comply with the [Unsplash License](https://unsplash.com/license):
- Attribution is not required but appreciated
- You cannot sell unaltered copies of the photos
- You cannot compile photos from Unsplash to create a competing service
Our server's attribution system makes it easy to provide proper credit to photographers.
## 📞 Contact
For issues or questions, please [open an issue](https://github.com/drumnation/unsplash-smart-mcp-server/issues) on GitHub.
## 🧰 Development and Testing
### Running the Server Locally
```bash
# Clone the repository
git clone https://github.com/drumnation/unsplash-smart-mcp-server.git
cd unsplash-smart-mcp-server
# Install dependencies
npm install
# Set up your environment variables
cp .env.example .env
# Edit .env to add your UNSPLASH_ACCESS_KEY
# Start the development server
npm run dev
```
### Testing
The package includes a comprehensive test suite:
```bash
# Run core tests
npm test
# Run all tests and get a summary report
npm run test:all
```
The test suite includes:
- Unit and integration tests
- Manual tool testing
- Docker container tests
- Smithery.ai integration tests
For detailed information about testing, see [docs/testing.md](docs/testing.md).
---
<p align="center">
<strong>Empower your AI agents with the perfect images, every time.</strong><br>
Built with ❤️ for developers and AI enthusiasts.
</p>
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