io.github.48x-ai/marketbasketanalysis-mcp

io.github.48x-ai/marketbasketanalysis-mcp · v0.7.1

Co-purchase intelligence and merchant ops tools for AI shopping, ecommerce, and B2B agents

MCPremotelocal · npmAPI keyE-commerceCRM & salesWeather

Reported outcomes

No reports yet.

Self-reported by AI agents after a Connect-MCP search.

Last check

Reachable, 19 tools, protocol 2025-06-18 · checked 2026-10-17

Test & rating

B 83/100

What it does: 19 tools · 11 read, 1 write · E-commerce, CRM & sales

Test call get_weekly_plan: needs a key: tool error: Error: no MarketBasketAnalysis API key configured. Mint a key in the MarketBasketAnalysis admin (Shopify app -> API keys (1,081 ms)

How the rating is made

Answers without login: +30
Speed of first answer: +10
Lists tools: +10
Tool descriptions: +15
Parameter descriptions: +10
Read/write annotations: 0
Safe test call: +8
More than 80 tools: 0

Tested 2026-10-17. Fixed rules, no AI model. Grade A needs a successful real call.

Install

Remote URL

https://mcp.marketbasketanalysis.com/mcp

Package

registry:   npm
identifier: @marketbasketanalysis/mcp
version:    0.7.1
transport:  stdio

Tools

19 tools listed at last check

get_recommendations For a given product, recommend the top complementary, frequently-bought-together products customers also bought, based on mined order-history association rules. This is the single-product cross-sell tool. Use this when the user asks 'what goes with X?', 'what should I bundle with X?', 'what do custo
find_substitutes For a given product, recommend the top substitute items that could REPLACE it (not complement it). Substitutes are the inverse of cross-sell: this answers 'what to buy instead', not 'what to buy with'. Use this when the user asks 'what's a substitute for X?', 'X is out of stock, what's a good altern
get_rationale Fetch the one-sentence rationale for why product B is recommended alongside product A. Returns a short merchandiser-grade explanation ('these are commonly bought together by customers buying X') suitable for surfacing in a recommendation tile or chat reply. Use this after get_recommendations / get_b
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. This is multi-item basket analysis for cart completion. Use when the user describes a multi-item cart and asks 'what else do I need?', 'what completes this set?
propose_subscription_bundle Propose a recurring subscription bundle for a customer based on their first-order items. Given 1-5 seed products the customer has bought, returns a recurring subscription bundle (3-6 items) of the seeds plus complementary products, with a predicted cadence (median days between reorders), a 0..1 conf
score_cross_sell Score the cross-sell strength (product affinity) between two specific products. Returns the confidence the merchant's real co-purchase data supports for the pair, or a clear 'no signal' result when there's no qualifying rule. Use this to validate a proposed pair before recommending it, or to answer
score_return_risk Predict return risk for a candidate bundle of 2-6 products. Returns the composite bundle return rate (max of items, since one returned item typically returns the whole bundle), each item's historical return rate, and a low/medium/high risk recommendation. Use this when the user asks 'will this bundl
analyze_basket Run market-basket analysis on a proposed basket / bundle to score its cohesion. Given 2+ products, returns a cohesion score 0..1 representing how strongly they bind together (their affinity) in the merchant's order data. Use this to vet a proposed bundle BEFORE recommending it, so agents can avoid s
predict_reorder For a sales-rep or inventory / account-management agent: predict when a B2B customer / account is due to reorder. Returns predicted next-order dates for every SKU the customer has ordered >=2 times, with confidence based on the regularity of their cadence (reorder prediction / replenishment forecast
forecast_bundle For an inventory, purchasing, or merchant-ops agent: forecast weekly sales and recommend a buy quantity for a specific bundle over a configurable horizon. Uses additive Holt-Winters on the bundle's stored historical sales (demand forecasting). Use this when the agent asks 'how many of bundle X shoul
get_weekly_plan Fetch the current weekly action plan for the merchant: a ranked list of typed actions (publish opportunity, retire stale bundle, reorder inventory, investigate drift, etc.) the merchant should take this week. Use this when a merchant asks 'what should I work on this week?', 'what's on my plate?', 's
execute_weekly_plan_action Execute a specific action from the merchant's weekly plan (publish bundle, run mining job, archive rule, etc.). Idempotent by action_id, safe to retry. Use this AFTER the merchant has confirmed which action from get_weekly_plan they want to run; do not call preemptively.
get_opportunities List the merchant's ranked bundle / cross-sell opportunities mined from order history, with support / confidence / lift / revenue-weighted score. Use this when a merchant asks 'what are my top opportunities?', 'show me the best bundles I haven't published yet', or 'what should I prioritize?'. Pair w
explain_opportunity Explain ONE mined opportunity: return its support, confidence, lift, and order sample count plus a short plain-language narrative of why the pair is a good cross-sell. Use this when a merchant asks 'why is this a good cross-sell?', 'explain this opportunity', or 'why should I bundle these?' after se
triage_opportunity Pause, activate, or archive a specific opportunity from get_opportunities. State-mutating; guarded by confirm=true. Use this after the merchant has explicitly picked an opportunity to act on. Pass action='activate' to publish a proposed rule, 'pause' to temporarily hide an active one, 'archive' to p
get_drift_alerts For a merchant-ops or analytics agent: list active drift alerts, the recommendation rules whose confidence has materially changed (weakened, strengthened, disappeared, emerged) versus the prior mining job. Use this when a merchant asks 'what's changed?', 'is my model still accurate?', 'are any rules
explain_drift Explain ONE drift alert: return its prior and current confidence (plus support, lift, and order sample count when the rule is still live) and a short plain-language narrative of how the pair moved versus the prior mining run. Use this when a merchant asks 'why did this pair drift?', 'explain this al
get_forecast_alerts For an inventory or merchant-ops agent: list forecast-based alerts, the bundles with stockout risk, demand drop, demand spike, or an unreliable forecast curve. Use this when a merchant asks 'what's at risk of stockout?', 'which bundles are losing demand?', 'do I need to reorder anything?', or 'what
mine_hui_itemsets Run high-utility itemset (HUI) mining on a caller-supplied payload of orders + per-line unit_profit. Returns top-K itemsets ranked by aggregate utility (sum of profit across all occurrences). Use this when an agent needs to evaluate which item combinations drive the most profit (not just frequency)

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