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sepehr071

digikala-mcp

by sepehr071

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    • F
      license
      A
      quality
      D
      maintenance
      Enables intelligent product discovery on Digikala (Iran's largest e-commerce platform) with bilingual search, query optimization, price filtering in Toomans, product details, recommendations, and AI-powered semantic search for clothing and accessories.
      5
      4
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    • F
      license
      C
      quality
      B
      maintenance
      Enables AI clients to search, fetch and cross-compare products, prices, sellers, offers, availability and specifications between Digikala and SnappShop, with tools for finding the best price or best-value offer using explicit filters and explainable reasoning. It also supports remote Streamable HTTP deployment so the same capabilities can be registered as a custom connector in clients such as Grok.
      11
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    • A
      license
      A
      quality
      C
      maintenance
      Enables LLM agents to retrieve live, accurately labeled data from DNS (dns-shop.ru) — city-specific pricing, product search with filters, ratings, reviews, store stock, and price history — while avoiding common data misinterpretations.
      5
      MIT
    • F
      license
      Not graded
      quality
      B
      maintenance
      Enables AI agents to query SoloTodo's product catalog, compare specs and prices, analyze price history, detect inflated offers, and review buyer evaluations through natural language.
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    TDQS

    A3.9/5.0

    Scored across 23 tools

    Disambiguation3/5

    Many product-discovery tools (dk_search, dk_category_products, dk_brand_products, dk_fresh_search, dk_find_cheapest, dk_best_for_budget, dk_best_sellers, dk_deals, dk_similar) overlap in returning product lists. The descriptions do a good job explaining when to use each and cross-referencing, but an agent still faces several plausible choices for a broad product query.

    Naming Consistency4/5

    All tool names use a consistent dk_ prefix and snake_case, which is predictable. However grammatical patterns vary (verb phrases like dk_find_cheapest, noun phrases like dk_price_history, adjective_noun like dk_best_sellers), so there is no strict verb_noun convention.

    Tool Count3/5

    23 tools is heavy for the core shopping-research purpose, sitting in the 16-25 borderline range. The broad domain (search, categories, product detail, reviews, price history, sellers, deals, Fresh, gold, location) explains some breadth, but several discovery tools feel like variants that could be consolidated.

    Completeness4/5

    The surface covers product discovery, detail, pricing history, reviews, Q&A, seller reputation, deals, Fresh, and location well. Gaps remain around transactional operations (cart, checkout, orders) and account-level features, but for a research-focused MCP it is largely complete.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues