Image Search MCP
MCP server for searching and retrieving stock images from Unsplash, Pexels, and Pixabay, with support for concurrent searches, normalized metadata, and image downloads.
README
MCP Image Search Server for Unsplash, Pexels & Pixabay
Image Search MCP is a Model Context Protocol server for searching Unsplash, Pexels, and Pixabay from one MCP client. Search one provider or all configured providers concurrently, return normalized image metadata, inspect image details, and download results.
Use it as an Unsplash MCP server, Pexels MCP server, Pixabay MCP server, or one unified MCP image search tool.
<p align="center"> <img src="images/landscape-mountains.jpg" alt="Stock image result available through the MCP image search server" width="800"> </p>
Features
- Search Unsplash, Pexels, and Pixabay through one MCP server
- Query multiple configured providers concurrently
- Filter searches to specific providers
- Normalize results into one consistent image schema
- Fetch detailed metadata for individual images
- Download images or return base64 image data
- Run locally over MCP or deploy with Streamable HTTP
- Fail clearly when a requested provider is invalid or not configured
Getting Started
Have an AI agent install it
Give your coding agent or AI assistant this install skill and let it configure the MCP for you:
1. Clone and install
git clone https://github.com/Serbyte-Development/image-search-mcp.git
cd image-search-mcp
python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
2. Get provider API keys
Configure one or more of these environment variables:
PEXELS_API_KEY
UNSPLASH_ACCESS_KEY
PIXABAY_API_KEY
API keys are available from:
- Pexels: https://www.pexels.com/api/
- Unsplash: https://unsplash.com/developers
- Pixabay: https://pixabay.com/api/docs/
You only need keys for the providers you want to use.
3. Add the MCP server to your client
{
"mcpServers": {
"image-search": {
"command": "/absolute/path/to/image-search-mcp/.venv/bin/python",
"args": [
"/absolute/path/to/image-search-mcp/image_search_mcp.py"
],
"env": {
"PEXELS_API_KEY": "your_pexels_key",
"UNSPLASH_ACCESS_KEY": "your_unsplash_key",
"PIXABAY_API_KEY": "your_pixabay_key"
}
}
}
}
Restart your MCP client after saving the configuration.
MCP Tools
search_stock_images
Search one or more configured providers.
Parameters:
query- search queryproviders- optional list containingpexels,unsplash, and/orpixabayper_page- results per provider, clamped to 1-50page- page numbersort_by-relevantornewestinclude_attribution- include provider attribution links when available
Example:
{
"query": "modern office interior",
"providers": ["unsplash", "pexels"],
"per_page": 10
}
get_image_details
Fetch detailed metadata for a provider-prefixed image ID such as pexels_123456.
download_image
Download an image by ID. Supported size values are thumbnail, small, medium, large, and original.
If output_path is omitted, the tool returns base64 image data instead of writing a file.
Result Format
Search results are normalized across providers and include fields such as:
{
"id": "pexels_123456",
"title": "Example image",
"url": "https://...",
"thumbnail": "https://...",
"width": 1920,
"height": 1080,
"photographer": "Photographer Name",
"source": "Pexels",
"license": "Provider license",
"tags": []
}
Run from the CLI
Install the local command:
pip install -e .
Then run:
image-search-mcp
Deploy with Streamable HTTP
app.py exposes a stateless Streamable HTTP MCP endpoint suitable for Vercel.
Set your provider API keys in the deployment environment, deploy the repository, then connect MCP clients to:
https://your-project.vercel.app/mcp
The example deployment does not add authentication. If you expose an MCP endpoint publicly, add appropriate access controls or expect requests to consume your provider API quotas.
Optional transport security settings:
IMAGE_SEARCH_MCP_ALLOWED_HOSTS
IMAGE_SEARCH_MCP_ALLOWED_ORIGINS
Both accept comma-separated values.
Development
Install development dependencies:
pip install -r requirements-dev.txt
Run lint, type checks, and unit tests:
make check PYTHON=.venv/bin/python
The repository also runs CI and CodeQL on pushes and pull requests to main.
Image Licensing
This project is MIT licensed, but images returned by the providers are governed by each provider's own current license and API terms. Review the applicable provider terms before using downloaded content in production.
Contributing
See CONTRIBUTING.md.
Security
See SECURITY.md for vulnerability reporting.
License
MIT - see LICENSE.
Developed & maintained by Serbyte Development.
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。