decathlon-mcp
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@decathlon-mcpsearch for a kayak and get details and reviews"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
README
This is an MCP server for decathlon.nl. The Netherlands website uses a different format than the rest of Decathlon (including IN) so this is a separate MCP server to deal with that.
Setup
You can set this up in claude code or your favourite mcp client in stdio mode with uv (recommended).
For Claude Code:
claude mcp add decathlon -- uv run --project /path/to/decathlon-mcp decathlon-mcpOr add it to your ~/.claude.json / client config directly:
{
"mcpServers": {
"decathlon": {
"command": "uv",
"args": ["run", "--project", "/path/to/decathlon-mcp", "decathlon-mcp"]
}
}
}Manual Setup
Requires Python >= 3.13 and uv.
git clone <repo-url>
cd decathlon-mcp
uv sync
uv run decathlon-mcpThis runs the server over stdio. Point any MCP client that supports stdio transport at the decathlon-mcp command.
Details
This MCP server implements four different tools:
search_suggestions(query)— autocomplete suggestions for a search term, including matching categories and popular queries.search_products(query, page)— product search. Returns a normalized summary per product: Decathlon ids (id,model_id,sku_id), title, brand, URL, image, price (with original price when discounted), online availability, sizes, rating and review count. Usesku_idwithget_product_detailsandmodel_idwithget_reviews.get_product_details(sku_ids[])— full details for one or more SKUs (batched): description, colors, size, weight, current price vs original price, seller, fulfillment options (store pickup / delivery / shipping), per-store stock availability, categories and sports.get_reviews(model_id, page, per_page)— customer reviews with aggregate stats (average rating, satisfaction %, star distribution) plus individual reviews with verified-purchase flags and sub-ratings per attribute (ease of use, value for money, etc.).
A typical agent flow is: search_products to find candidates → get_product_details to compare price/stock/sizes across variants → get_reviews to judge quality.
Implementation notes
The site soft-blocks bursts of requests (~1–2 min cooldown during which pages come back without product data), so requests are spaced at least 3 seconds apart and search_products retries with backoff when a response is missing data.
Product search uses the Next.js RSC protocol (RSC: 1 header on /search) since there is no public JSON search endpoint; its flight-data format is internal to Next.js and may need parser updates if Decathlon upgrades their stack. The product-details and reviews endpoints are plain JSON and more stable.
Disclaimer
This is not an official project. Currently limited to read-only access for obvious reasons.
This server cannot be installed
Maintenance
Resources
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