Upload base64-encoded media files to the YouCam API and return file_id(s).
| Name | Required | Description | Default |
|---|---|---|---|
| files | Yes | ||
| task_type | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden for behavioral disclosure. It mentions base64 encoding and file_id returns, but omits critical details like authentication requirements, file size limits, failure behavior, or whether the upload is synchronous.
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, front-loaded sentence with no wasted words. It delivers the core message efficiently, although it sacrifices detail for brevity.
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?
Despite having an output schema, the description is incomplete for a tool with two required parameters and an open-ended files array. Essential usage details like how to structure files and interpret task_type are missing, making it insufficient for an agent to invoke correctly without external information.
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 0%, so the description must compensate. It partially explains the 'files' parameter by noting base64-encoded media, but does not explain the 'task_type' parameter or the structure of objects within the files array.
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 tool uploads base64-encoded media files to the YouCam API and returns file_id(s). It identifies the specific action, resource, and output, but does not differentiate itself from sibling tools like 'File-Upload' or 'Get-Upload-API-Info'.
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 File-Upload or Get-Upload-API-Info. It lacks any context about prerequisites, task types, or exclusions.
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 are clearly distinct (e.g., AI-Object-Removal-Pro vs AI-Replace), but there is notable overlap among upload-related tools (File-Upload, Get-Upload-API-Info, upload_file) and among photo enhancement tools (Enhance, Color-Correction, Lighting) that could cause misselection. Template-listing tools are repetitive but each is tied to a specific generator.
Naming conventions are inconsistent: some tools use PascalCase with dashes (AI-Avatar-Generator), some use verb-first patterns (Get-Feature-Cost, Get-Running-Task-Status), and one uses lowercase snake_case (upload_file). The AI- prefix is consistent for many tools, but the overall pattern is mixed.
With 34 tools, the server feels overloaded. Many tools are variants of similar operations (e.g., numerous template listing tools) and could be consolidated or eliminated. The count exceeds the 25+ threshold for 'too many'.
The tool surface covers a broad range of AI media editing operations: photo and video generation, enhancement, background editing, face swap, object removal, and upload/status management. Minor gaps like video background removal (only replacement available) exist, but core workflows are well-supported.