digikala-mcp

Get Product Recommendations

get_product_recommendations

Read-only

Fetches store product suggestions for a product ID in upstream order, retaining ad flags, with an optional section key and result limit. Use it to review similar product suggestions, not personalized matches.

Instructions

Read store product suggestions in upstream order, retaining ad flags; cached 60 seconds.

Use list_product_recommendation_sections for other section keys. Limit is local (1–50). These are the store's suggestions, not personalized recommendations or guaranteed matches.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "product_id": "<product_id>"
    },
    "name": "get_product_recommendations"
  }
}

Input Schema

Name	Required	Default
`limit`	No
`product_id`	Yes
`section_key`	No	similar_products

Output Schema

Name	Required	Default
`error`	No
`title`	No
`products`	No
`warnings`	No
`product_id`	Yes
`source_url`	No
`observed_at`	No
`section_key`	No	similar_products
`source_count`	No
`cache_ttl_seconds`	No
`available_sections`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 28, 2026

TDQS

A4.1/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations only declare readOnlyHint and openWorldHint, so the description carries the behavioral load and does reasonably well: it discloses the 60-second cache TTL, that ad flags are preserved, that results are ordered upstream, and that the limit is applied locally rather than upstream. It does not explain pagination behavior past the local-limit remark or what 'upstream order' concretely means.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short sentences, front-loaded with the core action and ordering/caching facts, then the sibling routing, then the caveat. No filler. Slightly telegraphic ('Limit is local') but each clause carries information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return-value explanation is unnecessary, and annotations cover the safety profile. The description adds the caching, ordering, ad-flag, and section-key routing context an agent needs. The remaining gap is product_id semantics, the only required parameter.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate for three undocumented parameters. It partially does: it clarifies section_key usage via the sibling reference and describes limit as local with a 1–50 range. However, product_id (the only required parameter, with a restrictive numeric pattern) gets no explanation of expected format or source.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Read store product suggestions') plus scope qualifiers: upstream ordering, ad flags retained, and an explicit disclaimer that these are store suggestions rather than personalized recommendations. It also names the sibling list_product_recommendation_sections, so an agent can separate the two without inspecting schemas.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives an explicit routing rule: use list_product_recommendation_sections for other section keys. It also flags a constraint on limit (local, 1–50). It stops short of stating when a caller should prefer this tool over search_products or get_trend_snapshot-style alternatives, so it is clear context without full when/when-not coverage.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server