What does “MCP” mean in this server?
MCP stands for Model Context Protocol, a standard for exchanging data context between AI models and external tools. This server implements that protocol to provide grocery price data.
@Eneswunbeaten
Basic information
This tool helps you find the store offering the best price for a specific product among various chain markets in Turkey. The system fetches real-time data from different markets and returns the best price along with the corresponding store name.
No standard config provided
This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.
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A .NET‑based Model Context Protocol (MCP) server that compares grocery product prices across major Turkish markets in real time. It is designed for users who want to find the most affordable price for a product by querying MCP‑compatible AI assistants such as Claude or Cursor.
Clone the repository, restore dependencies with dotnet restore, and build with dotnet build. Then integrate the server into an MCP‑compatible client (e.g., Claude or Cursor) by adding a configuration pointing to the project .csproj file. Once connected, simply enter a product name in Turkish (e.g., “salatalık”, “domates”) to receive a multi‑market price comparison.
MCP stands for Model Context Protocol, a standard for exchanging data context between AI models and external tools. This server implements that protocol to provide grocery price data.
The README demonstrates integration with Claude (via `claude_desktop_config.json`) and Cursor (via its MCP settings). Any MCP‑compatible client can be configured to point to the server’s project file.
The server requires .NET 8.0 runtime. For Cursor, Node.js may also be needed if a “no tools found” error occurs. The project is built with the `ModelContextProtocol` NuGet package.
After integration, enter a product name in Turkish. The server will search across major Turkish grocery markets and return a comparison including product title, brand, price, and market name.
Each result includes four context types: `Title` (product info), `Brand` (brand name), `Price` (amount), and `Market` (store name).

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