Skip to main content
Glama
tzangms

shopline-mcp

by tzangms

list_customers

Retrieve a paginated list of customers from your Shopline store. Search by name, email, or phone to find specific customers.

Instructions

取得客戶列表,支援依關鍵字搜尋客戶。

【用途】 查詢特定客戶或瀏覽客戶清單。可用姓名、email、電話搜尋。 若要取得單一客戶的完整資訊(含儲值金、點數、等級),請改用 get_customer_profile。

【呼叫的 Shopline API】

  • GET /v1/customers(無搜尋條件時)

  • GET /v1/customers/search(有搜尋條件時)

【回傳結構】 dict 含 total_found, returned, customers[]。 每個 customer 包含 id, name, email, phone, tags, created_at。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
max_resultsNo最多回傳筆數
search_keywordNo搜尋關鍵字(姓名、email、電話)
Behavior4/5

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

No annotations are provided, so the description carries the burden. It discloses the underlying Shopline API endpoints (GET /v1/customers vs /v1/customers/search) and return structure (total_found, returned, customers[]). This adds valuable behavioral context beyond the basic listing, though it doesn't mention pagination or side effects.

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

Conciseness5/5

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

Well-structured with clear sections (用途, API, 回傳結構). Every sentence provides useful information, no redundancy, and it is front-loaded with the core purpose. Appropriate length for the tool's complexity.

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

Completeness5/5

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

Given no output schema, the description compensates by documenting the return structure. It covers the different API paths based on search, differentiates from the profile tool, and lists the customer fields returned. Complete for a list tool with two parameters.

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

Parameters4/5

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

Schema coverage is 100%, so baseline is 3. The description adds meaning by explaining that search_keyword triggers the search API and lists searchable fields (姓名、email、電話), which clarifies parameter behavior beyond the schema. max_results is not elaborated but the return structure hints at its role.

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?

Description states '取得客戶列表' (get customer list) with keyword search support, and explicitly distinguishes from get_customer_profile for full customer info. The verb+resource is specific and differentiates from the sibling tool.

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

Usage Guidelines5/5

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

Provides clear usage context: '查詢特定客戶或瀏覽客戶清單' (query specific customer or browse customer list). Explicitly names get_customer_profile as the alternative when full profile is needed, fulfilling the when-to-use and alternative guidance.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/tzangms/shoplinemcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server