Upscale an image with AI super-resolution (ESRGAN) for sharper enlargement. $0.02 per call. Input: an image via source URL. Params: width and/or height (target pixels; at least one required). Output: the enlarged image as a short-lived signed URL.
| Name | Required | Description | Default |
|---|---|---|---|
| params | Yes | ||
| source | Yes | Public https:// URL of the source image to process. |
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?
Annotations indicate readOnlyHint=false and openWorldHint=true. The description clarifies that the tool produces a 'short-lived signed URL' output, mentions pricing, and describes the AI process (ESRGAN). It does not contradict 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 three sentences, front-loaded with the primary purpose. Every sentence adds distinct value: purpose, pricing/input/params, and output. No redundancy or fluff.
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 tool's simplicity (2 params, no output schema), the description covers input, parameter constraints, output format, and pricing. It lacks details on supported image formats, size limits, or error scenarios, but is largely sufficient for a typical use case.
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?
The schema has 50% description coverage (only source has a description). The description adds semantics by clarifying that 'width and/or height' are target pixels and 'at least one required', which is not enforced in the schema. This provides valuable guidance beyond the schema.
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 'Upscale an image with AI super-resolution (ESRGAN) for sharper enlargement.' It uses a specific verb (upscale) and resource (image), and distinguishes from siblings like 'resize' by mentioning AI super-resolution.
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 specifies input requirements (source URL) and parameter constraints (at least one of width/height), but does not explicitly state when to use this tool vs alternatives like 'resize' or 'optimize'. No exclusions or usage context is provided.
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.
Each tool targets a distinct operation: optimization, pipeline processing, background removal, resizing, upscaling, and service discovery. No two tools overlap in purpose.
All tool names follow the consistent verb_noun pattern in lowercase snake_case (optimize, process, remove_background, resize, service_info, upscale).
With 6 tools, the server is well-scoped for an image processing service. Each tool earns its place, covering core operations, a pipeline composer, and metadata discovery.
The tool set directly offers essential transformations (compress, resize, background removal, upscale) and a pipeline tool (process) that can invoke additional ops via API, covering most common workflows. Missing direct tools for rotation or filters are minor gaps.