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  1. Home
  2. 🛒 E-Commerce
  3. Digikala
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Health: ActiveRecent health check succeeded.Last checked 10/15/2026, 12:45:14 AM

Digikala

InstallableWe know how to install it, but have not yet seen it complete a handshake. User RatingsBe the first to rate and review this MCP server!
View Repository30 GitHub StarsTotal stargazers on GitHub for the source repository (30 stars).
digikalae-commerceproduct-searchprice-trackingiran

Read-only MCP access to Digikala for product search, seller comparison, price history, reviews, deals, and related data.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.

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Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag — we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON ▾

Client Config & Setup

Choose your client or environment
Where:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "digikala": {
      "command": "uvx",
      "args": [
        "digikala-mcp"
      ]
    }
  }
}

💡 Settings → Developer → Edit Config, merge this into mcpServers, then fully quit and reopen Claude Desktop.

Install Tool Schemas (23) How it works Related FAQ Claim listing Alternatives🛒 More in E-Commerce Directory Badge

Overview

The Digikala MCP server connects AI agents to Digikala’s public product, seller, deal, and Fresh supermarket data. It provides 23 read-only tools for searching, filtering, comparing, and evaluating products, including prices, stock, reviews, offers, and price history. Run it locally over stdio with uvx, without an API key or Digikala account. Reach for it when an agent needs product research or price analysis, not purchasing, checkout, shipping-cost calculation, or login-only information.

Use cases

•Find the cheapest in-stock product matching a query
•Compare seller offers, specifications, and ratings
•Check whether a current price is near its recent low
•Browse Digikala Fresh supermarket deals
•Review seller performance before recommending a product

Key features

•Read-only Digikala product and seller access
•Search, category, brand, seller, and Fresh browsing
•Price history and shortlist repricing
•Product comparison, reviews, and customer questions
•Deals, installment plans, Plus plans, and gold prices

Capabilities & Tool Schemas (23) ~460 tokensApproximate context cost of this server’s tool schemas (~4 chars/token), before any tool is called. Actual usage depends on your client and model.Self-reported Self-reportedParsed from the repository README, not verified against a live server — may be incomplete or out of date.

Inspect callable tools, capabilities, and parameters exposed to AI agents by Digikala.

dk_search

Search by words with sort, price, brand, feature, color and seller filters; flags loose title matches

dk_find_cheapest

Cheapest in-stock real matches for a query, accessories dropped, one list

dk_best_for_budget

Best-rated real matches under a budget, rating weighted by number of ratings

dk_suggest

Autocomplete: better keywords, category codes and brand ids

dk_filters

Filter options of a category or search: features (OS, storage, ...), colors, brands, sellers, price range

dk_categories

Find category codes and main-category ids

How Digikala works

What Digikala MCP server does

The Digikala MCP server gives an AI agent read-only access to product and marketplace information from Digikala, Iran’s online store. It supports Persian and English queries and returns prices in Toman. The server does not log in, add items to a cart, place orders, or make payments, so it is intended for research and comparison rather than transaction workflows.

The available data covers the main Digikala catalogue, individual seller offers, Digikala Fresh supermarket listings, Incredible Offers, customer feedback, and selected related services. A typical research flow can identify the cheapest matching item, inspect its seller offers, and then check roughly 30 days of price history.

How it works

The Digikala MCP server runs on the local machine and communicates with an AI client through MCP over stdio. It then makes HTTPS requests to Digikala’s public API endpoints, which provide products, sellers, deals, and Fresh data. There is no hosted intermediary described in the project, and authentication is not required.

Product identifiers are numeric values taken from Digikala product links, such as the number after dkp-. These identifiers can be passed between tools for follow-up operations. Responses are compact JSON containing fields such as product title, brand, price, discount, stock, seller, rating, image URL, and product link where applicable. Ratings use a 0–5 scale, and unavailable ratings may be returned as null.

The server is suitable for agents that need to narrow a catalogue search, compare two to four products, re-check up to ten products, or assess whether a current price is near its recent low. Shipping cost is not available because Digikala calculates it at checkout.

Setup and configuration

Install uv, with Python 3.10 or newer available for the package, then run the Digikala MCP server with:

bash
uvx digikala-mcp

It can also be installed with pip install digikala-mcp and started with digikala-mcp. Claude Code can register it with claude mcp add digikala -- uvx digikala-mcp. Claude Desktop, Cursor, and VS Code can use a stdio configuration whose command is uvx and whose argument is digikala-mcp.

No API key or account is needed. If Digikala blocks the local network connection, the optional DIGIKALA_MCP_PROXY setting can specify an HTTP proxy, including one with an Iranian exit. The server uses no login credentials.

Tools and capabilities

The Digikala MCP server exposes tools in five broad groups:

  • Discovery: search, autocomplete suggestions, category and brand browsing, seller browsing, best sellers, filters, and Fresh supermarket search.
  • Selection: find the cheapest in-stock matching products, rank products within a budget, and remove accessory results from cheapest-match results.
  • Product analysis: inspect price, stock, specifications, seller offers, colors, warranties, shipping details, similar products, and side-by-side differences.
  • Market signals: view daily prices for about 30 days, identify recent lows and highs, re-price a shortlist of up to ten products, inspect reviews and questions, and find current deals.
  • Additional data: query Digipay installment offers, Digikala Plus plans, live 18k gold and coin prices, and address or coordinate conversion with Digikala location identifiers.

The confirmed category for this listing is 🛒 E-Commerce. Use the Digikala MCP server when the agent must gather current marketplace information; use another system when the task requires buying, account access, checkout, or shipping-cost computation.

Read the full README →View source on GitHub →

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars
30
Stargazers on the source repository.
Last commit
1d ago
Most recent push to the default branch.
Tools exposed
23
Callable tools this server registers over MCP.

Reviews

No reviews yet — be the first to share how this listing worked for you.

Frequently Asked Questions about Digikala

Digikala is an MCP server that connects AI agents to Digikala’s public product, seller, deal, and Fresh supermarket data. Its main tools search products, compare seller offers, inspect prices and stock, review price history, read customer feedback, find deals, and browse related marketplace information. It is read-only and needs no account or API key.

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Technical Specs & Signals

Category🛒E-Commerce
PricingFree
More technical detailsExpand ▾
TransportSTDIO
RuntimePython
AuthNo auth required
LicenseMIT
ClientsClaude Desktop, Cursor, Cline / VS Code, Windsurf, Claude Code, VS Code (GitHub Copilot), Zed, OpenAI Codex CLI, Gemini CLI, JetBrains AI Assistant, Roo Code, Continue
Last updatedOct 15, 2026
Views0
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars30
GitHub Star CountTotal stargazers on GitHub representing community popularity (30 stars).
Last commit1d ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Oct 13, 2026
57Quality signal: Good · 57/100How this signal is calculated ▾
Server availabilityNot measured

Not scored for repo-hosted servers — we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools26/30
Adoption & activity7/15
Community engagement0/10

A guidance signal from public completeness & health data — not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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