Convert format and/or compress an image. $0.005 per call. Input: an image via source URL. Params: format (webp|avif|jpeg|png|gif); quality (1-100, default 85 — lower is smaller). At least one of format/quality is required. Output: the optimized 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?
Discloses cost ($0.005 per call) and output nature ('short-lived signed URL'), adding value beyond annotations (readOnlyHint=false, openWorldHint=true). Does not mention rate limits or side effects but sufficient for context.
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?
Four concise sentences with zero waste, front-loaded purpose, efficient parameter description.
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?
Covers input, parameters, output (signed URL), and cost. No output schema, but description explains return value adequately. Could note error handling or expiry but acceptable for low complexity tool.
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?
Adds default value for quality (85) and confirms requirement of at least one parameter, supplementing the schema which already has enums and range but lacks defaults and dependency hints.
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?
Description uses specific verbs ('Convert format and/or compress') and identifies the resource ('image'), clearly distinguishing from siblings like 'resize' or 'remove_background'.
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?
Provides clear parameter constraints ('At least one of format/quality is required') and input type (source URL), but lacks explicit when-not-to-use or sibling comparisons.
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.