GET /ecommerce/stores/{id} — read one connected store. Public API preview.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | ||
| query | No | Optional query overrides for endpoints with sparse parameter schemas. | |
| brand_id | No | ||
| workspace_id | No | Workspace to operate in. Do not ask the user for this UUID — call aidelly_list_workspaces and use the `id` of the matching workspace. Optional for read operations; required when creating content. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / properties / workspace_id / descriptionAdded value: +"Workspace to operate in. Do not ask the user for this UUID — call aidelly_list_workspaces and use the `id` of the matching workspace. Optional for read operations; required when creating content."Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare this as a read-only, idempotent, non-destructive operation. The description adds minimal extra context: 'Public API preview' suggests possible instability. However, it does not disclose error responses, authentication requirements, or specific behavior (e.g., what happens if the store is not found). The description adds some value but not significant beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that includes the HTTP method, endpoint path, resource description, and status note. It is highly concise, front-loaded with the most important information, and contains no filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read operation with no output schema, the description is adequate but minimal. It identifies the resource but does not explain what the response contains, error conditions, or how to interpret the output. Given the tool's low complexity and the presence of annotations, the description is just sufficient but lacks completeness for a fully informed decision.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 50% (only 2 of 4 parameters have descriptions). The description does not mention any parameters or their meanings. It does not compensate for the lack of schema descriptions, leaving the agent to infer parameter usage from the path template alone. For a tool with moderate schema coverage, this is insufficient.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('GET' / read) and the resource ('one connected store' by ID). It distinguishes from sibling tools like aidelly_connect_ecommerce_store (connect), aidelly_disconnect_ecommerce_store (disconnect), aidelly_list_ecommerce_stores (list all), and aidelly_sync_ecommerce_store (sync) by specifying exactly what this tool does: read a single store.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when needing details of a specific ecommerce store, but it does not explicitly state when to use or avoid this tool, nor does it mention alternatives among siblings. There is no guidance on prerequisites (e.g., having a valid store ID) or when to prefer other tools like list_ecommerce_stores.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Many tools have overlapping purposes, especially in approvals and post updates. For example, aidelly_action_post_approval and aidelly_post_approvals_id_action both handle approval actions, while aidelly_get_approvals and aidelly_list_pending_approvals appear to serve similar listing functions. The proliferation of HTTP-route-style names with generic prefixes (get_approvals_id, patch_posts_id) further obscures distinctions.
The tool set mixes clean verb_noun names (create_post, list_posts) with HTTP-method-plus-path names (get_approvals_id, patch_posts_id, post_analytics_insights). There is no consistent pattern, and 'post' as a verb collides with the content post noun, creating confusion. The inconsistent conventions make it hard to predict tool names.
With 124 tools, this server vastly exceeds the typical MCP server scope and the calibration threshold (50+ is extreme). Even for a comprehensive platform API, such a large surface overwhelms agents and makes selection impractical. The count is a severe mismatch for a usable MCP tool set.
The tool surface is remarkably comprehensive, covering CRUD for posts, drafts, scheduled posts, tasks, reports, webhooks, workspaces, e-commerce stores, and many more. Advanced features like approvals, repurpose jobs, and content automations are also represented. Minor gaps exist (e.g., no explicit delete for regular posts, only cancel), but the domain is well covered overall.