schema-validator Connector for AI agents.
1 live capability
Enforce strict JSON schema validation for reliable agentic pipelines.
Waiting for input…
Why people use schema-validator
Stop broken payloads with Deterministic JSON Schema Gatekeeper
With this MCP, you set up a hard boundary. The engine checks every payload against your schema instantly. You get an immediate error report if something is wrong, so you fix it at the source before it ever touches your critical infrastructure.
What Vinkius changes
Your data stays clean and your pipelines stay running.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 6,100+ Connectors
- Real-world use case 01
Preventing API failures
An agent tries to send a string instead of an integer in a financial transaction, and `validate_json_schema` blocks it before the database is hit.
- Real-world use case 02
Email format enforcement
A user submits a form with an invalid email pattern, and `validate_json_schema` catches the error before it reaches your mailing service.
- Real-world use case 03
Array element verification
You need to ensure a list of IDs only contains strings; `validate_json_schema` rejects any payload containing integers or booleans at the source.
Complete set · 1capability
The complete schema-validator capability set.
These are the exact actions your AI can choose when you ask it to work with schema-validator.
01
1 capability in this set.
Part of 1 available through schema-validator.
- 01 Capability
Validate json schema
Checks if your JSON data matches your specific rules for types and structure. It catches missing fields or wrong types before they break your workflow.
Set up in minutes
One URL. Then ask schema-validator to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use schema-validator from the conversation.
Choose your client
Live previewAdvanced clients IDE · CLI
Claude · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_ktFyEC53FboFhcW2VPemJITVquvFY4zFFmc76f6c/mcp - Step 01
Open Connectors
In Claude Web or Claude Desktop, open Settings and choose Connectors.
- Step 02
Add the URL
Choose Add custom connector, name it schema-validator, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable schema-validator for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_ktFyEC53FboFhcW2VPemJITVquvFY4zFFmc76f6c/mcp - Step 01
Open MCP settings
On desktop, open Settings and MCP servers. On web, open your workspace app or connector settings.
- Step 02
Add the URL
Choose Add server with Streamable HTTP, or create a custom MCP app, then paste the schema-validator URL.
- Step 03
Save and start
Save the connection and enable schema-validator in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"deterministic-json-schema-gatekeeper": {
"url": "https://edge.vinkius.com/vk_preview_ktFyEC53FboFhcW2VPemJITVquvFY4zFFmc76f6c/mcp"
}
}
}- Step 01
Open MCP Settings
Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"
- Step 02
Add the server config
Paste the JSON configuration above into the mcp.json file that opens
- Step 03
Save the file
Cursor will automatically detect the new Connector
- Step 04
Start using schema-validator
Open Agent mode in chat and ask: "Using schema-validator, help me...". 1 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"deterministic-json-schema-gatekeeper": {
"url": "https://edge.vinkius.com/vk_preview_ktFyEC53FboFhcW2VPemJITVquvFY4zFFmc76f6c/mcp"
}
}
}- Step 01
Create MCP config
Create a .vscode/mcp.json file in your project root
- Step 02
Add the server config
Paste the JSON configuration above
- Step 03
Enable Agent mode
Open GitHub Copilot Chat and switch to Agent mode using the dropdown
- Step 04
Start using schema-validator
Ask Copilot: "Using schema-validator, help me...". 1 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"deterministic-json-schema-gatekeeper": {
"url": "https://edge.vinkius.com/vk_preview_ktFyEC53FboFhcW2VPemJITVquvFY4zFFmc76f6c/mcp"
}
}
}- Step 01
Open MCP Settings
Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"
- Step 02
Add the server
Paste the JSON configuration above into mcp_config.json
- Step 03
Save and reload
Windsurf will detect the new server automatically
- Step 04
Start using schema-validator
Open Cascade and ask: "Using schema-validator, help me...". 1 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"deterministic-json-schema-gatekeeper": {
"url": "https://edge.vinkius.com/vk_preview_ktFyEC53FboFhcW2VPemJITVquvFY4zFFmc76f6c/mcp"
}
}
}- Step 01
Open Cline MCP Settings
Click the Connectors icon in the Cline sidebar panel
- Step 02
Add remote server
Click "Add Connector" and paste the configuration above
- Step 03
Enable the server
Toggle the server switch to ON
- Step 04
Start using schema-validator
Ask Cline: "Using schema-validator, help me...". 1 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add deterministic-json-schema-gatekeeper --transport http "https://edge.vinkius.com/vk_preview_ktFyEC53FboFhcW2VPemJITVquvFY4zFFmc76f6c/mcp"- Step 01
Install Claude Code
Run npm install -g @anthropic-ai/claude-code if not already installed
- Step 02
Add the Connector
Run the command above in your terminal
- Step 03
Verify the connection
Run claude mcp to list connected servers, or type /mcp inside a session
- Step 04
Start using schema-validator
Ask Claude: "Using schema-validator, show me...". 1 tools are ready
Where the request belongs
Work schema-validator can move forward.
The AI engineer who's tired of debugging broken JSON payloads at 3am. The backend developer managing complex API integrations. The data engineer ensuring structural standards across autonomous agentic workflows.
AI Engineer
Building and testing autonomous pipelines that require strict, predictable data contracts.
Backend Developer
Managing complex API integrations and ensuring payload integrity between microservices.
Data Engineer
Ensuring that incoming streams of JSON data adhere to predefined structural standards before processing.
Build the capability set
Add more capabilities.
Each Connector adds new actions and data without changing how you work.
Browse ConnectorsSalesforce
Connect your Salesforce CRM to any AI agent. query records with SOQL, manage accounts, contacts, opportunities, run reports, and perform CRUD operations.
Okta
Equip your AI agent with Okta Identity Cloud to manage users, groups, and seamless authentication effortlessly.
OpenAI
Use GPT-4o, DALL-E 3, embeddings, fine-tuning, and moderation as capabilities inside your AI agent workflows.
Anthropic
Access Claude models via Anthropic API. send messages, count tokens, manage batches and discover models from any AI agent.
X Ads (Twitter)
Connect your X Ads account to any AI agent. audit campaigns, analyze line item performance, and pull engagement reports through natural conversation.
Box
Store, share, and collaborate on files securely with enterprise-grade cloud content management and governance controls.
Bring your own AI
Change the model, client or framework. Keep 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 schema-validator.
The practical details behind the request, access and result.
How can I prevent errors in my AI agent pipelines with Deterministic JSON Schema Gatekeeper?
You use it as a checkpoint to validate all incoming and outgoing data against strict rules, catching errors before they propagate.
Does Deterministic JSON Schema Gatekeeper slow down my API calls?
No, it uses a lightweight V8 engine designed for microsecond latency, ensuring your pipelines stay fast.
Can I use Deterministic JSON Schema Gatekeeper for regex validation?
Yes, you can enforce specific text patterns like emails or phone numbers directly in your schema definition.
What happens if my JSON is malformed when using Deterministic JSON Schema Gatekeeper?
The MCP will return a detailed diagnostic array pointing out exactly where the structure failed and which field was broken.
Can Deterministic JSON Schema Gatekeeper handle complex nested objects?
Yes, it validates deep structural hierarchies and ensures every nested field adheres to your defined schema.
Does this MCP work with Cursor or Windsurf?
Yes, you can connect this MCP to any compatible client like Cursor, Windsurf, or VS Code via Vinkius.
Why use this instead of Zod or Ajv?
Zod is fantastic for codebases but creates massive dependency bloat when distributed in edge-runtime micro-agents. This MCP implements a deterministic schema checker using pure V8 logic, delivering identical structural protection with 0ms spin-up time and zero external dependencies.
What validation rules does it support out of the box?
It supports data types (string, number, array, boolean, object), required flag, string boundaries (minLength, maxLength, pattern), number boundaries (min, max), and even array item typing (e.g., ensuring an array contains only strings).
Will it crash if the JSON is completely broken?
No. The engine employs aggressive try-catch boundary catching. If a payload is unparseable or maliciously formatted, it gracefully intercepts the panic and returns a structured JSON error diagnostic without taking the server down.
One connection away
Give your agent a direct line to schema-validator.
Connect schema-validator once. Keep it beside 6,100+ managed Connectors when the next task needs more.
Explore every Connector No credit card required · Free tier available