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Klydo MCP Server
Fashion discovery MCP server for Indian Gen Z.
Enables AI assistants like Claude to search and discover fashion products from Klydo — India's Gen-Z quick tech fashion commerce platform based in Bangalore.
✨ Features
- 🔍 Search Products — Search fashion items with filters (category, gender, price range)
- 📦 Product Details — Get complete product info including images, sizes, colors, ratings
- 🔥 Trending Products — Discover what's popular right now
- 📝 Structured Logging — Debug-friendly logs with Loguru
- ⚡ Fast & Cached — In-memory caching for quick responses
🚀 Quick Start
Installation
#### Option 1: Install from PyPI (Recommended)
# Using pip
pip install klydo-mcp
# Or using pipx (isolated environment)
pipx install klydo-mcp
# Or using uvx (no installation needed)
uvx --from klydo-mcp klydo#### Option 2: Install from Source
# Clone the repository
git clone https://github.com/myselfshravan/klydo-mcp.git
cd klydo-mcp
# Install dependencies with uv
uv syncUsage with Claude Desktop
#### If installed via PyPI (pip/pipx)
Add to your Claude Desktop configuration:
- macOS:
~/Library/Application Support/Claude/claude_desktop_config.json - Windows:
%APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"klydo": {
"command": "klydo"
}
}
}#### If using uvx (recommended for easy updates)
{
"mcpServers": {
"klydo": {
"command": "uvx",
"args": ["--from", "klydo-mcp", "klydo"]
}
}
}#### If installed from source
{
"mcpServers": {
"klydo": {
"command": "uv",
"args": ["--directory", "/path/to/klydo-mcp", "run", "klydo"]
}
}
}Then restart Claude Desktop.
Run Standalone
uv run klydo🛠️ MCP Tools
search_products
Search for fashion products.
| Parameter | Type | Description |
|---|---|---|
query | string | required — Search terms (e.g., "black dress", "nike shoes") |
category | string | Filter by category (e.g., "dresses", "shoes") |
gender | string | Filter by gender ("men" or "women") |
min_price | int | Minimum price in INR |
max_price | int | Maximum price in INR |
limit | int | Max results (default 10, max 50) |
get_product_details
Get complete product information.
| Parameter | Type | Description |
|---|---|---|
product_id | string | required — Product ID from search results |
Returns: Full details — images, sizes, colors, ratings, and purchase link.
get_trending
Discover what's hot rn 🔥
| Parameter | Type | Description |
|---|---|---|
category | string | Category filter |
limit | int | Max results (default 10, max 50) |
⚙️ Configuration
Copy .env.example to .env and customize:
# Request settings
KLYDO_REQUEST_TIMEOUT=30
KLYDO_CACHE_TTL=3600
# Debug mode (set to false in production)
KLYDO_DEBUG=false
# API token for klydo.in (required)
KLYDO_KLYDO_API_TOKEN=your-token📁 Project Structure
klydo-mcp/
├── src/klydo/
│ ├── __init__.py
│ ├── server.py # MCP server entry point
│ ├── config.py # Configuration (Pydantic Settings)
│ ├── logging.py # Loguru configuration
│ ├── models/
│ │ └── product.py # Product, Price models
│ └── scrapers/
│ ├── base.py # Scraper protocol (interface)
│ ├── cache.py # In-memory cache with TTL
│ └── klydo_store.py # Klydo.in API client
├── tests/ # Test suite
├── .github/workflows/ # CI/CD pipelines
├── pyproject.toml
└── README.md🧪 Testing
# Run all tests
uv run pytest
# Run with verbose output
uv run pytest -v
# Run specific test file
uv run pytest tests/test_models.py🔧 Development
# Install dev dependencies
uv sync --dev
# Run linting
uv run ruff check src/
# Format code
uv run ruff format src/
# Run the server locally
uv run klydo🤝 Contributing
We welcome contributions! Please see our Contributing Guide for details.
- Fork the repository
- Create a feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'Add amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
🔐 Security
For security issues, please see our Security Policy.
📄 License
MIT License — see LICENSE for details.
🏢 About Klydo
Klydo is a Bangalore-based startup building quick tech fashion commerce for Gen-Z (18-32 age group). We're making fashion discovery seamless, fast, and accessible. This MCP server extends our platform to AI assistants, enabling natural language fashion search.
Backed by innovation. Built for Gen-Z. Made in India. 🇮🇳
Made with ❤️ in Bangalore, India