Digikala MCP Server
Related Servers
Alternatives to Digikala MCP Server
No user-submitted related servers found.
Related Servers
- FlicenseNot gradedqualityDmaintenanceEnables LLM-powered search with Elasticsearch, including query planning, expansion, and intelligent filtering for e-commerce.-
- FlicenseNot gradedqualityDmaintenanceEnables semantic search and natural language product recommendations using ChromaDB vector store and Azure OpenAI embeddings. Supports multi-filter search by category, brand, and price with 8 specialized MCP methods for intelligent product discovery.-
- FlicenseAqualityDmaintenanceEnables AI-powered shopping assistance by analyzing natural language shopping queries and automating product searches on multiple e-commerce platforms.13-
- AlicenseBqualityBmaintenanceEnables AI agents to automatically discover, extract, and retrieve verified high-resolution product images and product links from e-commerce sites via a universal extraction pipeline with pluggable search backends, caching, and CDN-aware upscaling.4MIT
- AlicenseAqualityDmaintenanceKlarna-style product discovery for AI shopping agents. Makes product catalogs machine-readable so AI agents can search, compare, and purchase products programmatically.6MIT
- AlicenseNot gradedqualityBmaintenanceExposes product catalog and semantic search as tools for an LLM agent, enabling natural language product recommendations based on intent rather than keyword matching.1MIT
TDQS
Scored across 5 tools
The tools have mostly distinct purposes, with clear boundaries: get_optimized_keywords_and_categories for keyword/category optimization, get_product_details for detailed product info, get_product_recommendations for similar products, search_products for category-based searches, and search_text_lenz for semantic visual searches. However, search_products and search_text_lenz both involve searching, which could cause minor confusion, though their descriptions clarify different use cases (category-based vs. semantic/visual).
Tool names follow a consistent verb_noun pattern with underscores (e.g., get_optimized_keywords_and_categories, search_products), making them predictable and readable. There is a minor deviation with search_text_lenz, which includes a brand name 'Text-Lenz' in the noun part, but it still fits the overall naming convention without mixing styles like camelCase.
With 5 tools, this server is well-scoped for an e-commerce product search and information domain. Each tool serves a specific function (e.g., optimization, details, recommendations, searches), and none feel redundant or unnecessary, providing a balanced set for typical agent workflows in this context.
The tool set covers key operations like searching, getting details, and recommendations, but there are notable gaps. For example, there are no tools for user account management (e.g., login, cart operations), purchase-related actions (e.g., add to cart, checkout), or content management (e.g., reviews, ratings). While the domain appears focused on product discovery and information, these omissions could limit agent functionality in full e-commerce scenarios.