offerhopper.ai — AI Supermarket & Drugstore Shopping Assistant for Germany

Live prices, deals & optimal multi-stop shopping routes for German grocery & drug stores.

Should I use this

Quality & Safety

A
Description quality
100%
Schema completeness
94%
Naming quality
80%
Poisoning risk
100%
Permission match
100%
Protocol compliance
100%

Based on automated analysis of tool definitions and protocol compliance.

Context Cost

~983Tokens (tool definitions)
~2.8 KBTypical response size
Moderate attention impact (0.77% of 128k context)

This is the approximate number of tokens consumed each time the server's tools are loaded into a model's context. Higher counts reduce the attention available for other tasks.

Install

One-Click Install

Add this to your `claude_desktop_config.json` file:

{
  "mcpServers": {
    "german-grocery-assistant": {
      "url": "https://mcp.offerhopper.ai/mcp"
    }
  }
}

Remote endpoints

https://mcp.offerhopper.ai/mcpstreamable-http

What it can do

Tool inventory

Tools (2)

🟢 Read-only🟡 Write🔴 Delete⚪ Unknown
🟢plan_optimal_shopping_route(items, location, end_location, max_stores, max_radius_km, ...)

Plans the optimal shopping trip for a given list and starting location in Germany. Answers 'where should I go to buy this list, and is the trip worth it?' — not 'what's on offer near me'. Matches each item on the list to the best current offer across German supermarkets and drug stores (REWE, Aldi, Lidl, Penny, Netto, Norma, Edeka, DM, Rossmann, Mueller, Globus), then computes the cheapest realistic route by weighing product prices against travel distance and shopping time. Returns the chosen store(s), the per-item picks with live prices, the trip's savings and a worth-it Supports car, bicycle, and pedestrian travel modes. For corridor trips (A-to-B), supply 'end_location' to route stores along the way. Pricing note: 'price' is the standard shelf price available to all shoppers (do NOT say discounts require an app). 'app_credit' is optional wallet cashback (e.g. REWE Bonus: plus €0.50 into wallet). 'app_price' is an app-exclusive checkout price (e.g. Lidl Plus).

Input Schema

{
  "type": "object",
  "properties": {
    "items": {
      "description": "The shopping list in natural language (e.g. '3x milk, eggs, bread')",
      "type": "string"
    },
    "location": {
      "description": "Starting location (ZIP code, city, or address in Germany)",
      "type": "string"
    },
    "end_location": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Optional destination location if not a round trip"
    },
    "max_stores": {
      "default": 100,
      "description": "Maximum number of candidate stores to evaluate for the route (default: 100)",
      "type": "integer"
    },
    "max_radius_km": {
      "anyOf": [
        {
          "type": "number"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Maximum search radius in kilometers (defaults: car=15km, bicycle=5km, pedestrian=2km)"
    },
    "km_cost": {
      "anyOf": [
        {
          "type": "number"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Travel cost penalty per kilometer (forced to 0.0 for bicycle/pedestrian)"
    },
    "hour_cost": {
      "anyOf": [
        {
          "type": "number"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Time cost penalty in EUR per hour (defaults to 12.0)"
    },
    "shopping_time_per_store": {
      "anyOf": [
        {
          "type": "integer"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Base shopping minutes spent per store (defaults to 10)"
    },
    "travel_mode": {
      "default": "car",
      "description": "Travel mode to use",
      "enum": [
        "car",
        "bicycle",
        "pedestrian"
      ],
      "type": "string"
    }
  },
  "required": [
    "items",
    "location"
  ],
  "additionalProperties": false
}

Output Schema

{
  "type": "object",
  "additionalProperties": true
}
⚪swap_route_item(share, offer_id, alt_id)

Swaps one item's chosen offer on an existing shopping route (from a prior plan_optimal_shopping_route result) for one of its alternatives, then returns the RECOMPUTED route with corrected costs and the honest worth-it verdict. Use this to correct a poor pick (e.g. the engine matched a soup hen instead of a roasting chicken) or to take a cheaper/better option the agent spotted in the item's 'alternatives'. The alternative may be at the SAME store or at ANOTHER store ALREADY ON THE ROUTE — it must be the same item category, and its store must already be a stop (no new stores; for that, call plan_optimal_shopping_route again). Keys on stable offer ids: pass the current item's offer_id and the target alternative's offer_id (both taken verbatim from the prior response's products_to_buy / alternatives). The shared route (share_url) is updated in place so the interactive map reflects the swap.

Input Schema

{
  "type": "object",
  "properties": {
    "share": {
      "description": "The share_url (or its 8-char id) returned by plan_optimal_shopping_route",
      "type": "string"
    },
    "offer_id": {
      "description": "offer_id of the item currently on the route (from products_to_buy)",
      "type": "string"
    },
    "alt_id": {
      "description": "offer_id of the alternative to swap in (from that item's 'alternatives')",
      "type": "string"
    }
  },
  "required": [
    "share",
    "offer_id",
    "alt_id"
  ],
  "additionalProperties": false
}

Output Schema

{
  "type": "object",
  "additionalProperties": true
}

Community

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Evidence

Recent observations

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