INDIVIDUAL MCP TOOL
score_cross_sell
Score the cross-sell strength (product affinity) between two specific products.
LIVE ENDPOINT
https://mcp.marketbasketanalysis.com/mcp
Connect to this endpoint to inspect the live schema for score_cross_sell and invoke it with your own arguments.
Indexed input schema
{}Risk classification
Inferred read-only · medium confidence · heuristic, not a guarantee.
- No write-capable action terms were found; this is not proof that invocation has no side effects.
Parent server
CONNECT WITH APPROVAL
Client installation
Review this server and its permissions before adding it. Secret placeholders must be set locally.
Codex
~/.codex/config.toml
[mcp_servers.marketbasketanalysis]
url = "https://mcp.marketbasketanalysis.com/mcp"
enabled = true
Claude Code
.mcp.json
{
"mcpServers": {
"marketbasketanalysis": {
"type": "http",
"url": "https://mcp.marketbasketanalysis.com/mcp"
}
}
}
Claude Desktop
Settings → Connectors → Add custom connector
Name: marketbasketanalysis
Remote MCP URL: https://mcp.marketbasketanalysis.com/mcp
Add this remote URL as a custom connector in Claude Desktop. Availability depends on the user plan and workspace policy.
Cursor
.cursor/mcp.json
{
"mcpServers": {
"marketbasketanalysis": {
"url": "https://mcp.marketbasketanalysis.com/mcp"
}
}
}
Visual Studio Code
.vscode/mcp.json
Add to Visual Studio Code{
"servers": {
"marketbasketanalysis": {
"type": "http",
"url": "https://mcp.marketbasketanalysis.com/mcp"
}
}
}
Generic MCP
Client-specific MCP configuration
{
"name": "marketbasketanalysis",
"transport": "streamable-http",
"url": "https://mcp.marketbasketanalysis.com/mcp"
}
MCP Inspector
Run the official MCP Inspector locally and enter the indexed Streamable HTTP endpoint.
Related tools
get_recommendations— For a given product, recommend the top complementary, frequently-bought-together products customers also bought, based on mined order-history association rules.find_substitutes— For a given product, recommend the top substitute items that could REPLACE it (not complement it).get_rationale— Fetch the one-sentence rationale for why product B is recommended alongside product A.get_bundle_for_cart— Given a list of products already in the cart, recommend products that frequently bundle with the cart to complete a high-confidence bundle.propose_subscription_bundle— Propose a recurring subscription bundle for a customer based on their first-order items.score_return_risk— Predict return risk for a candidate bundle of 2-6 products.analyze_basket— Run market-basket analysis on a proposed basket / bundle to score its cohesion.predict_reorder— For a sales-rep or inventory / account-management agent: predict when a B2B customer / account is due to reorder.