ah-mcp

Albert Heijn: Bonus Offers

ah_get_bonus_offers

Read-only

Find Albert Heijn bonus and discount offers for this week or next week; filter by keyword or products bought before.

Instructions

Get Albert Heijn bonus/promotional offers. Use this (not ah_search_products) when the user asks what is on bonus/sale/discount. Returns this week's bonus by default; set period='next' for next week's bonus, which AH publishes a few days before the new bonus week starts. Supports optional keyword filter to find e.g. cheese on bonus: set query='kaas'. Set previously_bought=true for offers on products the user bought before (AH's 'Eerder gekocht'). Group deals (e.g. '2+1 gratis', 'Alle yoghurt 25% korting') have no id but a bonus_segment_id — pass that to ah_get_bonus_group_products to see the individual products in the group. Returns id, bonus_segment_id, title, original_price, bonus_price, discount_percentage, bonus_mechanism. When you mention a product or recipe from the result, link its name to its url.

Input Schema

TableJSON Schema

Name	Required	Description
`limit`	No	Maximum number of results to return (default 20)
`query`	No	Optional keyword filter (Dutch or English) applied client-side, e.g. 'kaas', 'vlees', 'bier'
`period`	No	Which bonus week to return: 'current' (default) or 'next'
`previously_bought`	No	Only offers on products the user bought before

Output Schema

TableJSON Schema

Name	Required	Description	Default
`offers`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedv1.3.1Oct 5, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "additionalProperties": false,
+  "properties": {
+    "offers": {
+      "items": {
+        "additionalProperties": false,
+        "properties": {
+          "bonus_mechanism": {
+            "type": "string"
+          },
+          "bonus_price": {
+            "type": "number"
+          },
+          "bonus_segment_id": {
+            "type": "string"
+          },
+          "discount_percentage": {
+            "type": "number"
+          },
+          "id": {
+            "type": "number"
+          },
+          "original_price": {
+            "type": "number"
+          },
+          "title": {
+            "type": "string"
+          },
+          "url": {
+            "type": "string"
+          }
+        },
+        "required": [
+          "title"
+        ],
+        "type": "object"
+      },
+      "type": "array"
+    }
+  },
+  "required": [
+    "offers"
+  ],
+  "type": "object"
+}

First observedv1.0.0Oct 5, 2026

TDQS

A4.8/5.0

Behavior5/5

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

Annotations only declare readOnlyHint, so the description carries the useful behavioral load: default period is the current week, period='next' data is published a few days before the bonus week begins, and group deals lack an id but expose a bonus_segment_id. These are non-obvious traits an agent could not infer from the schema or annotations.

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?

Well front-loaded: purpose first, then disambiguation, then parameter nuances, then return fields and the linking instruction. It is dense and mostly earns its length, though the enumerated return fields and the url-linking instruction add bulk that a tighter description could shed.

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

Completeness5/5

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

Given an output schema exists, return values need not be restated, yet the tool's behavior, filtering options, week semantics, and the hand-off to the group-products sibling are all covered. Nothing needed to invoke it correctly is missing.

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 100%, so baseline is 3, but the description adds domain meaning: period='next' timing semantics, a concrete Dutch query example ('kaas'), and the AH-specific label 'Eerder gekocht' for previously_bought. It does not add syntax beyond the schema, hence 4 rather than 5.

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 verb+resource ('Get Albert Heijn bonus/promotional offers') and immediately distinguishes itself from ah_search_products. The scope (weekly bonus offers, group vs single deals) is precise enough that an agent can choose it without opening the schema.

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

Usage Guidelines5/5

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

Explicitly names the tool NOT to use ('not ah_search_products') and the trigger condition ('what is on bonus/sale/discount'). It also routes the agent onward to ah_get_bonus_group_products with the exact condition (group deals carrying a bonus_segment_id but no id). Both alternatives and their selecting conditions are stated.

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