List tracked competitor domains for the workspace.
| Name | Required | Description | Default |
|---|---|---|---|
| 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. | |
| include_archived | No |
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 readOnly hint, open world hint, and no destructive behavior. The description adds that the tool returns 'tracked competitor domains,' which is consistent but does not disclose additional behavioral traits like pagination, ordering, or rate limits. Given annotation coverage, the description is adequate but not enriching.
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 concise sentence, front-loading the core purpose. It is efficient and avoids fluff, though it sacrifices parameter context. A balance of brevity and completeness would improve it.
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?
Given 4 parameters, no output schema, and the tool's moderate complexity, the description is too brief. It does not explain expected return format, pagination, or the meaning of 'tracked competitor domains.' The annotations help but don't replace the need for richer context.
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%; two parameters (brand_id, include_archived) lack descriptions. The tool description adds no parameter information, failing to compensate for missing schema details. For instance, it doesn't explain the role of 'query' or filters like 'include_archived,' leaving agents to guess.
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 'List tracked competitor domains for the workspace.' uses a specific verb ('list') and resource ('competitor domains'), clearly distinguishing it from sibling tools like 'add_competitor' or 'list_workspaces'. It avoids tautology by adding 'tracked' and 'domains', making the purpose unambiguous.
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 provides no guidance on when to use this tool versus alternatives, such as when listing other entities (e.g., posts, workspaces) or when adding competitors. It does not specify prerequisites or context for invocation, leaving the agent to infer usage.
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.