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Vinkius

JSON Schema Validator Connector for AI agents.

3 live capabilities

Ensure your AI-generated data matches your production API schemas.

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Why people use JSON Schema Validator

JSON Schema Validator: Stop LLM Hallucinations from Breaking Your Backend

With this Connector, you put a guardrail in front of your data flow. Your agent generates the JSON, the Connector checks it against your schema, and if it fails, the agent sees the exact error—like 'field price must be a number'—and can try again. You get clean, predictable data every single time.

  • Claude
  • ChatGPT
  • Gemini
  • Cursor
  • Visual Studio Code
  • Windsurf

What Vinkius changes

You get guaranteed data integrity for every LLM output.

Use it from Claude, ChatGPT, Cursor or another AI client you already have.

One account · 5,900+ Connectors

  1. Real-world use case 01

    Preventing broken webhooks

    An engineer uses this to make sure an AI agent's webhook payload contains every required field before the system tries to process the payment.

  2. Real-world use case 02

    Cleaning batch data

    A data scientist validates thousands of rows of AI-generated product descriptions to ensure they don't exceed the 500-character limit.

  3. Real-world use case 03

    Safe API integration

    A developer uses this to verify that a user profile generated by an AI client matches their OpenAPI specification exactly.

Complete set · 3capabilities

The complete JSON Schema Validator capability set.

These are the exact actions your AI can choose when you ask it to work with JSON Schema Validator.

Capability set01 / 01

01—03

3 capabilities in this set.

Part of 3 available through JSON Schema Validator.

  1. 01 Capability

    Lint json schema

    Performs structural linting on a JSON Schema

  2. 02 Capability

    Validate json document

    Validates a JSON document against a JSON Schema

  3. 03 Capability

    Evaluate schema compatibility

    Evaluates if a new schema is compatible with a base schema

Set up in minutes

One URL. Then ask JSON Schema Validator to work.

Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use JSON Schema Validator from the conversation.

Choose your client

Live preview
Advanced clients IDE · CLI

Claude · Web + desktop

Official guide ↗

Connector URL · ready to paste

Streamable HTTP
https://edge.vinkius.com/vk_preview_wcVN6ru2KXI4lPbS9isndc7khYOy12YDatbPmrNo/mcp
  1. Step 01

    Open Connectors

    In Claude Web or Claude Desktop, open Settings and choose Connectors.

  2. Step 02

    Add the URL

    Choose Add custom connector, name it JSON Schema Validator, and paste the URL above.

  3. Step 03

    Turn it on in chat

    Select +, open Connectors, and enable JSON Schema Validator for the conversation.

Where the request belongs

Work JSON Schema Validator can move forward.

Built around the request

This is for the backend engineer who is tired of debugging 'Internal Server Errors' caused by messy AI data. It's for developers building production apps where data accuracy is non-negotiable.

01

Backend Engineer

Uses this to ensure AI-generated webhooks or payloads don't crash the production database.

02

Data Engineer

Validates large batches of LLM-generated records against a strict SQL schema before ingestion.

03

Full-Stack Developer

Connects AI outputs to frontend components while guaranteeing that every required field exists.

Build the capability set

Add more capabilities.

Each Connector adds new actions and data without changing how you work.

Browse Connectors
JSON Schema Strict Validator logo
01 3 capabilities

JSON Schema Strict Validator

Perform deterministic JSON validation against Draft-07 and 2020-12 schemas with strict property enforcement.

View Connector
JSON Payload Depth and Size Limiter logo
02 3 capabilities

JSON Payload Depth and Size Limiter

Validate JSON payloads against strict nesting depth and byte size constraints to prevent parser crashes.

View Connector
Protobuf to JSON Schema Transpiler logo
03 3 capabilities New

Protobuf to JSON Schema Transpiler

Convert Protocol Buffer (.proto) definitions into valid JSON Schema objects deterministically.

View Connector
XML Tag Structure Compliance Checker logo
04 1 capability New

XML Tag Structure Compliance Checker

Validate XML tag integrity, nesting hierarchy, and tag-to-text density.

View Connector
JSON Schema Validator and Flattener logo
05 3 capabilities New

JSON Schema Validator and Flattener

Strictly validate JSON against schemas and flatten nested structures using dot notation.

View Connector
JSON Schema Function Call Validator logo
06 1 capability New

JSON Schema Function Call Validator

Verify that LLM-generated JSON function calls strictly adhere to your defined JSON Schemas.

View Connector

Bring your own AI

Change the model, client or framework. Keep JSON Schema Validator connected.

  • Claude
  • ChatGPT
  • Gemini
  • Cursor
  • VS Code
  • Windsurf
  • ZCode
  • Cline
  • Zed
  • Continue
  • Kiro
  • Roo Code
  • Zencoder
  • Goose
  • Void
  • Augment Code
  • Amp
  • Qodo
  • Tabnine
  • Pieces
  • Sourcegraph Cody
  • JetBrains
  • Warp
  • Amazon Q
  • Antigravity
  • BoltAI
  • Raycast
  • Jan
  • LM Studio
  • AnythingLLM
  • Open WebUI
  • Msty
  • Cherry Studio
  • LibreChat
  • TypingMind
  • Chorus
  • 5ire
  • n8n
  • LangChain
  • LlamaIndex
  • CrewAI
  • Vercel AI SDK

Before you connect

Questions about JSON Schema Validator.

The practical details behind the request, access and result.

How does JSON Schema Validator work with my AI agent?

Your agent sends a JSON string to the Connector, which checks it against your rules. It then reports back whether the data is correct or lists the specific errors it found.

Can JSON Schema Validator check for missing fields?

Yes. It identifies any required properties that the AI left out of the JSON payload so you can ensure your data is complete.

Will JSON Schema Validator help with OpenAPI schemas?

It's designed to work with them. You can use your OpenAPI definitions as the schema to ensure AI outputs match your API contracts.

How does JSON Schema Validator handle nested JSON?

It handles deeply nested objects perfectly, checking every level of your JSON to ensure types and constraints are met throughout.

What happens if the AI output is invalid?

The Connector returns a specific list of errors. You can then show these errors to your agent so it knows exactly how to fix the JSON.

Can I use JSON Schema Validator for data integrity?

That is its primary purpose. It provides a mathematical guarantee that the data your agent produces follows your required structure.

Does it support Draft-07?

Yes, it perfectly implements JSON Schema Draft-07.

Will it point out specific errors?

Yes, it returns the exact path and validation failure reason.

Can it validate OpenAPI specs?

Yes, it evaluates all nested types and definitions.

What does `validate_json_document` do?

It checks a JSON document against a provided schema and returns validation errors with exact JSON Pointers.

How can I find logical errors in my schema?

You can use the lint_json_schema capability to detect unreachable constraints or conflicting types within your schema definition.

Can I check if a new schema version breaks my existing integration?

Yes, the evaluate_schema_compatibility capability compares a base schema with a new one to identify any breaking changes.

One connection away

Give your agent a direct line to JSON Schema Validator.

Connect JSON Schema Validator once. Keep it beside 5,900+ managed Connectors when the next task needs more.

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