Skip to main content

Klydo MCP Server

CI PyPI version Python 3.11+ License: MIT MCP Compatible

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

# 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 sync

Usage 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"
    }
  }
}
{
  "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.

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.

  1. Fork the repository
  2. Create a feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes (git commit -m 'Add amazing feature')
  4. Push to the branch (git push origin feature/amazing-feature)
  5. 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

Metadata

Release files for klydo-mcp 0.1.6

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for klydo-mcp 0.1.6
File Size Uploaded
klydo_mcp-0.1.6.tar.gz 119.6 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for klydo-mcp 0.1.6
File Interpreter ABI Platform
klydo_mcp-0.1.6-py3-none-any.whl Python 3 none any Details

Total release size: 144.7 kB

Release files / klydo_mcp-0.1.6.tar.gz

Download URL klydo_mcp-0.1.6.tar.gz
Size 119.6 kB
Tags Source
SHA-256 checksum
How to use checksums
5ae5fdadf1a4cc467b5172d03afbbd8fab774e8ee0c4bf190ac5ca340c885015
BLAKE2b-256 checksum
How to use checksums
6586a5aaf506021e9aff33dfd7baa8d43a7718f0635a66825c6d4c6517d98f92
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/6.1.0 CPython/3.13.7

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Feb 22, 2026.

Transparency log

Release files / klydo_mcp-0.1.6-py3-none-any.whl

Download URL klydo_mcp-0.1.6-py3-none-any.whl
Size 25.1 kB
Tags Python 3
SHA-256 checksum
How to use checksums
c5ff3ec614e175688875a2f8b68c60434890fba7c6622e3aa518a1f9f02035f9
BLAKE2b-256 checksum
How to use checksums
8aa734296380ab757fe694b94911153251c814cb5b148d47122f168ee158256b
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/6.1.0 CPython/3.13.7

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Feb 22, 2026.

Transparency log

Release history Release notifications | RSS feed

This release

0.1.6 This release

2 release files

0.1.4

2 release files

0.1.3

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page