JSON to TOON MCP Server
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
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| convert_json_to_toonB | Convert JSON data to TOON (Token-Oriented Object Notation) format for efficient LLM token usage |
| convert_toon_to_jsonB | Convert TOON format back to JSON data |
| analyze_token_savingsC | Analyze potential token savings when converting JSON to TOON |
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
Each tool has a clearly distinct purpose: analyze_token_savings is for analysis, convert_json_to_toon is for one-way conversion, and convert_toon_to_json is for reverse conversion. There is no overlap or ambiguity between these functions.
All tool names follow a consistent verb_noun pattern (analyze_token_savings, convert_json_to_toon, convert_toon_to_json) with clear, descriptive terms. There are no deviations in naming style.
Three tools are well-scoped for a JSON/TOON conversion server, covering analysis and bidirectional conversion. It feels slightly minimal but reasonable, as core operations are present without bloat.
The tool set provides complete coverage for the domain: analysis of token savings, conversion from JSON to TOON, and conversion back from TOON to JSON. There are no obvious gaps for the stated purpose of efficient LLM token usage.