schema-tools
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 | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| generate_json_schemaA | Generate a JSON Schema from one or more sample JSON values. Infers types, required fields, formats (email, date, URI, UUID), and detects enum patterns from multiple examples. |
| generate_typescriptA | Generate TypeScript interfaces and types from JSON data or a JSON Schema. Handles nested objects, arrays, optional fields, enums, union types, and Record types. |
| validate_schemaA | Validate data against a JSON Schema. Returns detailed error messages with JSON path, expected type, actual value, and the violated keyword (type, required, format, pattern, minimum, etc.). |
| mock_from_schemaA | Generate realistic mock data from a JSON Schema. Uses smart field-name detection to produce contextual values: email fields get valid emails, name fields get realistic names, dates get ISO strings, etc. Supports all JSON Schema types and constraints. |
| diff_schemasA | Compare two JSON Schemas and identify all differences: added/removed/changed fields, type changes, constraint changes (min/max, patterns, enums). Classifies each change as breaking or non-breaking for backwards compatibility analysis. |
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 5 tools
Each tool has a clearly distinct purpose: generation from data, generation from schema, validation, mocking, and diffing. No overlap or ambiguity between tool responsibilities, so an agent should reliably select the correct tool for a given task.
All tool names follow a consistent verb_noun pattern (generate_, validate_, mock_, diff_). The verbs are specific and descriptive, and the noun consistently refers to the primary artifact (schema or types). No mixed conventions or vague naming.
With exactly 5 tools covering the core schema lifecycle, the count is tight and focused. Each tool earns its place, and the number is within the ideal range for a utility server without being overly minimal or bloated.
The set covers the major schema operations: creating schemas from data, generating types for coding, validating data, generating mocks, and comparing schemas for evolution. Together they form a coherent, end-to-end toolkit with no obvious dead ends or missing critical operations.