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frigolog-haccp vs Fetch

Сравнение двух MCP-серверов по фактам. Выбери подходящий для Claude Desktop, Claude Code или Cursor.

Frigolog HACCP MCP is a public Model Context Protocol server that gives AI agents (Claude, ChatGPT, Perplexity, custom agents) accurate, sourced answers about F

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Web content fetching and conversion for efficient LLM usage.

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Сравнение

Параметрfrigolog-haccpFetch
ЦенаFreeFree
Установки1
Рейтинг
Проверен
HostedHosted
Инструменты
Категорияaiai
АвторnaimterracheCommunity
Репозиторийmodelcontextprotocol/servers

Когда выбрать frigolog-haccp

Frigolog HACCP MCP is a public Model Context Protocol server that gives AI agents (Claude, ChatGPT, Perplexity, custom agents) accurate, sourced answers about French food safety regulations. Four read-only tools: • get_haccp_temperatures — Regulatory temperatures for storage, cooling and serving of food products in France. Sources: arrêté du 21 décembre 2009, règlement (CE) n° 852/2004, règlement (CE) n° 853/2004. • get_documents_controle_ddpp — Documents required during a French DDPP (Direction Départementale de la Protection des Populations) sanitary inspection, by establishment type (restaurant, butcher, baker, cheese shop, fishmonger, ice cream shop, caterer, wine merchant, collective catering). • get_regles_dlc — Rules for the use-by date (DLC — Date Limite de Consommation) of in-house preparations in French restaurants and food crafts, per the Guide des Bonnes Pratiques d'Hygiène (DGAL). • compare_solutions_haccp — Factual comparison of the main HACCP software on the French market: Frigolog, ePackPro, Octopus HACCP, Traqfood, Kooklin, BackResto, Hygiene Up. Pricing, engagement, hardware imposed, AI features, IoT sensors, support, 3-year cost. Endpoint: https://frigolog.fr/api/mcp Transport: HTTP + JSON-RPC 2.0 (no SSE, no auth) License: MIT Maintained by Frigolog (https://frigolog.fr). Disclosure: Frigolog is one of the seven solutions listed in compare_solutions_haccp. The dataset is based on publicly available info from each editor's website. Pull requests welcome to correct any inaccuracy.

Когда выбрать Fetch

Web content fetching and conversion for efficient LLM usage.

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