Skip to main content
Glama

Shopline Connector

shopline_connector
Read-onlyIdempotent

SHOPLINE ecommerce data: store profile, orders, refunds, products, inventory, locations, customers, returns, fulfillment orders, and discount-code price rules. Read-only first-party connector using merchant-scoped OAuth. When the user asks for a visual, trend, comparison, or recap, call chart_render with the numeric values returned by this connector. If the connector result includes a verified chart_provenance token, the same authenticated user may pass it as provenance_token within 15 minutes, on any replica, and map every value to its exact source_path so chart_render preserves verified provenance. Without a valid connector receipt, chart_render labels values as unverified_model_data. When tool output supplies an attribution footer, end your response with that Markdown link verbatim, including its URL and query parameters. Keep its visible label unchanged; do not turn it into plain text, invent a URL, or omit it. Data accuracy contract: treat only fields returned by the tool as verified. Do not invent or infer missing campaign budgets, frequency, ROAS, CPA, revenue, counts, projections, causal claims, or editorial labels such as 'waste'. Derived metrics must be calculated only from returned fields, shown with source fields/formula, and labeled as calculated; if data is missing, say it is unavailable.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionYesget_store_info: Get connected SHOPLINE store identity, currency, timezone, status, domain, language, and contact fields. Read-only | list_orders: List SHOPLINE orders with totals, payment and fulfillment state, customer, line items, refunds, and pagination cursor. R | get_order: Get one SHOPLINE order by id using the documented orders ids filter. Returns totals, customer, line items, shipping, ful | get_order_summary: Calculate a bounded SHOPLINE order summary over a creation-time window. Returns source values and explicit formulas for | get_order_refunds: Get refunds associated with one SHOPLINE order, including refund line items, adjustments, and transactions_v2. Read-only | list_products: List SHOPLINE products and embedded variants, including SKU, price, inventory item id, and aggregate inventory quantity | get_product: Get one SHOPLINE product by id with variants, prices, SKUs, media, and inventory fields. Read-only | get_inventory_items: Get SHOPLINE inventory-item metadata by one or more IDs: cost, SKU, tracking, shipping requirement, and variant id. Read | get_inventory_levels: Get SHOPLINE inventory availability for inventory item IDs, optionally filtered to location IDs. Read-only | list_locations: List SHOPLINE inventory and fulfillment locations with address and active/default status fields. Read-only | list_customers: List SHOPLINE customers with profile, order count, total spent, subscription state, date filters, and pagination cursor | search_customers: Search SHOPLINE customers by fuzzy name/email/phone/address or the documented structured customer query syntax. Read-onl | get_customer: Get one SHOPLINE customer by id with profile, order count, total spent, addresses, and subscription state. Read-only | list_returns: Get SHOPLINE returns by return id or order id with status, reasons, and returned line items. At least one identifier is | list_fulfillment_orders: List assigned SHOPLINE fulfillment orders, including destination, location, holds, line items, supported actions, and pa | list_discount_code_price_rules: List SHOPLINE discount-code price rules. This endpoint is not a complete automatic-discount inventory; that limitation i
paramsNoAction-specific parameters. get_store_info: none | list_orders: {limit?: integer, page_info?: string, financial_status?: string, fulfillment_status?: string, status?: string, created_at_min?: string, created_at_max?: string} | get_order: {order_id: string} | get_order_summary: {created_at_min?: string, created_at_max?: string, max_pages?: integer} | get_order_refunds: {order_id: string, limit?: integer} | list_products: {limit?: integer, page_info?: string, status?: string, title?: string, vendor?: string, created_at_min?: string, created_at_max?: string} | get_product: {product_id: string} | get_inventory_items: {ids: array} | get_inventory_levels: {inventory_item_ids: array, location_ids?: array} | list_locations: none | list_customers: {limit?: integer, page_info?: string, since_id?: string, ids?: string, created_at_min?: string, created_at_max?: string, updated_at_min?: string, updated_at_max?: string} | search_customers: {limit?: integer, page_info?: string, query?: string, query_param?: string, order?: string} | get_customer: {customer_id: string} | list_returns: {id?: string, order_id?: string} | list_fulfillment_orders: {limit?: integer, assignment_status?: string, location_ids?: array, page_info?: string, since_id?: string} | list_discount_code_price_rules: {limit?: integer, page_info?: string, created_at_min?: string, created_at_max?: string, starts_at_min?: string, starts_at_max?: string, ends_at_min?: string, ends_at_max?: string}

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.8/5.0
Behavior5/5

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

Annotations already declare readOnlyHint/idempotentHint/non-destructive, and the description goes well beyond them: merchant-scoped OAuth, the 15-minute provenance-token window valid on any replica, the unverified_model_data fallback when no receipt exists, a mandatory verbatim attribution footer, and a data-accuracy contract forbidding invented or inferred fields. This is unusually rich behavioral disclosure for a connector.

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

Conciseness3/5

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

Purpose is correctly front-loaded, but the body is long and dominated by agent meta-instructions (chart_render handoff, provenance token mechanics, attribution footer wording, accuracy contract) that are only tangentially about selecting or invoking this tool. Several sentences could be moved to shared system guidance without loss.

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?

For a 16-action read-only connector with no output schema, the description covers data domains, access model, downstream chart integration, and an explicit accuracy contract, which is close to complete. Pagination behavior and rate limits are not addressed, though the schema references pagination cursors per action.

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 100% — the action enum documents all 16 actions and the params object spells out every action-specific parameter — so the baseline is 3. The description adds no parameter-level detail (no syntax, format, or defaults) beyond what the schema already carries.

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

Purpose4/5

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

The first sentence names the platform (SHOPLINE) and enumerates the resource domains covered — store profile, orders, refunds, products, inventory, locations, customers, returns, fulfillment orders, discount-code price rules — plus the access model ('Read-only first-party connector using merchant-scoped OAuth'). That is clear resource scope, but there is no action verb and the domain list largely mirrors the schema's action enum, so it stops short of a full 5.

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

Usage Guidelines3/5

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

The description gives explicit routing guidance downstream ('When the user asks for a visual, trend, comparison, or recap, call chart_render...') but says nothing about when to choose this connector versus a sibling connector, or about prerequisites beyond OAuth. Usage is only implied by the data domains listed, so this is minimum-viable guidance.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources