Digikala MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| get_optimized_keywords_and_categoriesA | Get optimized search keywords and relevant categories. IMPORTANT: Always call this with BOTH Persian (Farsi) and English queries separately, as the API responds differently to each language and Farsi typically yields better, more comprehensive results. |
| search_productsA | Search for products within a specific category with filtering and sorting. Returns 20 products per page. CRITICAL WORKFLOW: ALWAYS call get_optimized_keywords_and_categories FIRST to get the category_id for your search - this API requires it. Use the keyword-category pairs from that response. Search with BOTH Persian (Farsi) and English keywords separately - they produce different results, with Farsi often being more comprehensive. All prices in TOOMAN (1 Tooman = 10 Rials). |
| get_product_detailsA | Get comprehensive product information including specifications, expert reviews, customer feedback, and buy suggestions. Use this when you need detailed information about a specific product. |
| get_product_recommendationsA | Get similar products and related category recommendations. Use this when a product is close but not exactly what you need, to explore similar alternatives. |
| search_text_lenzA | AI-powered semantic search using Text-Lenz. Exceptional for clothing, accessories, wearables, and shoes. Use 2-3 word visual descriptions (e.g., 'red summer dress', 'black running shoes'). Understands natural language and context. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
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