test-1
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| TINYPNG_API_KEY | Yes | Your TinyPNG API key |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| compress_local_imageC | Compress a local image file |
| compress_remote_imageC | Compress a remote image file by giving the URL of the image |
| resize_imageC | Resize an image file |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 3 tools
The tools are mostly distinct with clear purposes: compress_local_image and compress_remote_image handle compression for different image sources, while resize_image performs a different operation. However, the two compression tools could potentially be confused by an agent since they serve similar functions (compression) but differ only in input source, which might lead to misselection if the agent doesn't carefully parse the descriptions.
All tool names follow a consistent verb_noun pattern using snake_case, with clear action-object naming: compress_local_image, compress_remote_image, and resize_image. The naming is predictable and readable throughout the set.
With only 3 tools, the server feels somewhat thin for an image processing domain, as it covers only compression and resizing. While the tools are focused, the count is borderline low, potentially missing other common operations like format conversion, cropping, or filtering that agents might expect.
The tool surface covers basic image operations (compression and resizing) but has notable gaps for a complete image processing workflow. Missing operations include format conversion, cropping, filtering, or metadata handling, which could cause agent failures when trying to perform common image tasks beyond the provided scope.