Israel Grocery MCP

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add_recipe_to_cart

Parse a recipe or URL, match ingredients to products, and add them to a Shufersal or Tiv Taam cart using cheapest, preferred-store, or single-store buying.

Instructions

Parse a recipe, find best-matching products, and add them to a cart.

Args:
    recipe_text: Recipe text or URL.
    store_id: Which store to add to ("shufersal" or "tivtaam").
              If omitted, uses your preferred_store or the cheapest per item.
    strategy: "cheapest" — buy each item from its cheapest store.
              "preferred_store" — use your preferred_store for everything.
              "single_store" — use store_id for everything (requires store_id).
    confirm_all: If True, add low-confidence matches without pausing.

Input Schema

TableJSON Schema

Name	Required	Default
`store_id`	No
`strategy`	No	cheapest
`confirm_all`	No
`recipe_text`	Yes

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 13, 2026

TDQS

A4.3/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the burden and does disclose meaningful behavior: low-confidence matches normally pause, confirm_all suppresses that pause, and store selection falls back to preferred_store or cheapest. It omits auth/login prerequisites (notable given login_* siblings) and failure behavior, but the confidence-pause semantics are genuinely useful disclosure.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The summary line is front-loaded and the Args block is terse and scannable. The docstring-style formatting is slightly verbose but every line carries semantic weight for an undocumented schema.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return values need not be explained, and all four parameters are covered. The main gap is that login/authentication requirements are unstated for a cart-mutating tool, but overall the description is sufficient to invoke it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% with no enums, so the description must compensate, and it does: it defines all four parameters including accepted values for store_id and the three strategy modes with their interaction with store_id. It does not restate defaults, but the mapping of values to behavior is clear.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific multi-step action (parse recipe, match products, add to cart) on a concrete resource. It is clearly distinguishable from siblings like compare_recipe and add_to_cart, which do one of those steps only.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explains the selection logic between strategies and the fallback when store_id is omitted (preferred_store or cheapest per item). It does not explicitly say when to prefer this tool over plan_recipe_ingredients or compare_recipe, so it stops short of full alternative routing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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