list_projectsThe user's saved logos, coins and generated meshes, newest first. Optional title search and kind filter.
| Name | Required | Description | Default |
|---|---|---|---|
| kind | No | ||
| page | No | ||
| query | No | Match against the title |
| Name | Required | Description | Default |
|---|---|---|---|
| page | Yes | ||
| total | Yes | ||
| projects | Yes | ||
| totalPages | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / $schemaPrevious value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"Output schema / $schemaPrevious value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"Output schema / properties / projects / items / properties / inputType / anyOfRemoved value: -[
- {
- "type": "string"
- },
- {
- "type": "null"
- }
-]Output schema / properties / projects / items / properties / inputType / typeAdded value: +[
+ "string",
+ "null"
+]Output schema / properties / projects / items / properties / updatedAt / anyOfRemoved value: -[
- {
- "type": "string"
- },
- {
- "type": "null"
- }
-]Output schema / properties / projects / items / properties / updatedAt / typeAdded value: +[
+ "string",
+ "null"
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish read-only, idempotent, and non-destructive behavior. The description adds useful behavioral context beyond those annotations: newest-first ordering, the saved-project scope, and the available optional filters. It does not mention pagination behavior, but the output schema and annotations cover much of the operational picture.
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 front-loads the core action and scope, then adds the sort order and filters. Every word earns its place, and there is no repetition of information already in the annotations or schema.
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 the rich annotations (read-only, idempotent, non-destructive), an output schema, and a clear schema for kind/page/query, the description is complete enough for an agent to invoke the tool correctly. The only minor gap is explicit alternative routing, but that is not required for successful execution.
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 description coverage is only 33%, so the description partially compensates by explaining 'title search' and 'kind filter' for the query and kind parameters. However, it says nothing about the page parameter, and the schema provides only default/min/max for it, so the coverage gap is not fully closed.
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 states a specific verb and resource: list the user's saved projects, scoped to 'logos, coins and generated meshes', and adds the sort order 'newest first'. This clearly distinguishes it from sibling tools like get_project (single project) and list_generations (generation history).
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 when to use the tool: whenever the user's saved projects are needed, with optional title search or kind filtering. However, it never explicitly names alternatives or says when not to use it, so the agent must infer usage context from the resource scope.
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.
Most tools target distinct resources, but several overlapping pairs exist: search/list_projects both find projects by title, fetch/get_project both return project details, and upload_logo_image/request_logo_image_upload are two upload paths. The descriptions help clarify boundaries, but an agent could still misselect.
Tool names overwhelmingly follow a clear verb_noun snake_case pattern (create_, list_, get_, update_, delete_). Minor deviations like bare 'fetch' and 'search', plus the mixed '3d' in generate_3d_model vs '3D' in descriptions, keep it from being perfectly consistent.
At 31 tools, this exceeds the 25+ threshold where agent tool selection becomes cognitively heavy. While the server covers a broad platform, several tools are near-redundant and could be consolidated, making the count feel inflated.
The surface covers project lifecycle, sharing/publishing, AI generation, uploads, materials, and account/plan management quite thoroughly. Minor gaps exist, such as no direct create_coin_project tool and no deletion for generation runs, but these are workable.