Schema Bridge 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
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 |
|---|---|
| schema_convertA | Convert any database schema (SQL DDL, Prisma) or JSON payload into production-ready Zod schemas, TypeScript interfaces, or Python Pydantic v2 models. |
| schema_generate_mockA | Generate realistic, relational synthetic mock JSON data (names, emails, dates, UUIDs, currencies, statuses) from any SQL, Prisma, or JSON schema. |
| schema_validateA | Validate a JSON data payload against a schema definition (SQL, Prisma, or JSON Schema) and report detailed type errors and missing fields. |
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 distinct purpose: validating data, converting schemas, and generating mock data. There is no overlap or ambiguity between them.
All tools follow the consistent pattern `schema_<verb>`, using clear snake_case naming. The action is immediately identifiable from the name.
Three tools cover a focused schema-related workflow without unnecessary bloat or missing essentials. The count is well-suited to the server's stated purpose.
The toolset covers the core lifecycle of schema handling: validation, conversion, and mock generation. No significant gaps are apparent for the described domain.