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将标准 JSON Schema 的 JSON/YAML 定义转换为可直接在 TypeScript 项目中使用的 Zod 运行时校验代码，支持嵌套结构、数组、枚举和常见校验规则
用三种语言从你的代码中调用此工具。
curl -X POST 'https://api.elysiatools.com/zh/api/tools/json-schema-to-zod-schema-converter' \
-H 'Content-Type: application/json' \
-d '{"schemaInput":"{\n \"type\": \"object\",\n \"required\": [\"email\"],\n \"properties\": {\n \"email\": { \"type\": \"string\", \"format\": \"email\" },\n \"age\": { \"type\": \"integer\", \"minimum\": 18 }\n }\n}","sourceFormat":"json","rootSchemaName":"userSchema","namingStyle":"camel","outputMode":"schema-and-type","includeDescriptions":true}'以 JSON 形式 POST 提交输入参数。文件类型参数需先单独上传。
POST https://api.elysiatools.com/zh/api/tools/json-schema-to-zod-schema-converter| 参数名 | 类型 | 必填 | 说明 |
|---|---|---|---|
| schemaInput | textarea | 是 | — |
| sourceFormat | select | 否 | — |
| rootSchemaName | text | 否 | — |
| namingStyle | select | 否 | — |
| outputMode | select | 否 | — |
| includeDescriptions | checkbox |
将此工具加入你的 Model Context Protocol 服务，让 AI 智能体可以列出并调用它。
将以下内容加入你的 MCP 客户端配置：
{
"mcpServers": {
"elysiatools-json-schema-to-zod-schema-converter": {
"name": "json-schema-to-zod-schema-converter",
"description": "将标准 JSON Schema 的 JSON/YAML 定义转换为可直接在 TypeScript 项目中使用的 Zod 运行时校验代码，支持嵌套结构、数组、枚举和常见校验规则",
"baseUrl": "https://api.elysiatools.com/mcp/sse?toolId=json-schema-to-zod-schema-converter",
"command": "",
"args": [],
"env": {},
"isActive": true,
"type": "sse"
}
}
}连接到 SSE 端点后，列出已开放的工具：
{
"jsonrpc": "2.0",
"id": 1,
"method": "tools/list"
}通过工具 id 调用，参数由其参数表构建：
{
"jsonrpc": "2.0",
"id": 2,
"method": "tools/call",
"params": {
"name": "json-schema-to-zod-schema-converter",
"arguments": {
"schemaInput": "{\n \"type\": \"object\",\n \"required\": [\"email\"],\n \"properties\": {\n \"email\": { \"type\": \"string\", \"format\": \"email\" },\n \"age\": { \"type\": \"integer\", \"minimum\": 18 }\n }\n}",
"sourceFormat": "json",
"rootSchemaName": "userSchema",
"namingStyle": "camel",
"outputMode": "schema-and-type",
"includeDescriptions": true
}
}
}有问题或反馈？请联系 [email protected]
| 否 |
| — |
文本结果
{
"result": "Processed text content",
"error": "Error message (optional)",
"message": "Notification message (optional)",
"metadata": {
"key": "value"
}
}