json-to-model
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
| prompts | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| setup_authD | – |
| generate_model_from_apiD | – |
| list_supported_languagesD | – |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| json-to-model | Interactive setup for json-to-model: asks for language, login URL/params, refresh token URL. |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 3 tools
Each tool has a clearly distinct purpose: setup_auth handles authentication, generate_model_from_api performs the core generation, and list_supported_languages provides a utility. There is no overlap or ambiguity.
All tools follow a consistent verb_noun pattern in snake_case: setup_auth, generate_model_from_api, list_supported_languages. The naming convention is uniform and predictable.
With 3 tools, the set is well-scoped for a focused json-to-model server. Each tool serves a necessary role (auth, generation, languages), and the count falls within the ideal 3-15 range.
The core generation and prerequisite authentication are covered, and language discovery is useful. However, the server name suggests generating from raw JSON, while the tool only mentions API, so there may be a gap for direct JSON input.