Tool Call Schema Validator Connector for AI agents.
3 live capabilities
Enforce strict JSON schema validation for agentic capability calls
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Why people use Tool Call Schema Validator
Stop agent hallucinations with capability Call Schema Validator
With this MCP, that guesswork disappears. You insert a validation step into your agent's loop. The moment the agent generates a capability call, the MCP inspects it. If it's wrong, you get a clear report of exactly what failed and where. You stop fixing broken code and start building reliable agents.
What Vinkius changes
You get a reliable way to guarantee your agent's output matches your system's input requirements.
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 from hallucinated types
An agent tries to send a string to a price field that requires a float.
- Real-world use case 02
Validating complex nested user profiles
When an agent generates a large user object, the MCP verifies every nested field and array element against the master schema.
- Real-world use case 03
Enforcing strict enum selections
An agent attempts to use an unsupported status code.
Complete set · 3capabilities
The complete Tool Call Schema Validator capability set.
These are the exact actions your AI can choose when you ask it to work with Tool Call Schema Validator.
01—03
3 capabilities in this set.
Part of 3 available through Tool Call Schema Validator.
- 01 Capability
Check type conformity
Performs a granular check of a single value against a specific type constraint. Use this for quick, individual field validation.
- 02 Capability
Summarize validation report
Aggregates multiple validation errors into a human-readable summary. It makes it easy to see all mistakes at once.
- 03 Capability
Validate capability call
Checks if a specific set of capability arguments matches a provided schema definition. It is the primary way to verify entire payloads.
Set up in minutes
One URL. Then ask Tool Call Schema Validator to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Tool Call 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_fjeQqEAkovq6wv5QOSR8yluR5fVJhGSyYuZMaIIw/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 Tool Call Schema Validator, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable Tool Call Schema Validator for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_fjeQqEAkovq6wv5QOSR8yluR5fVJhGSyYuZMaIIw/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 Tool Call Schema Validator URL.
- Step 03
Save and start
Save the connection and enable Tool Call Schema Validator in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"tool-call-schema-validator": {
"url": "https://edge.vinkius.com/vk_preview_fjeQqEAkovq6wv5QOSR8yluR5fVJhGSyYuZMaIIw/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 Tool Call Schema Validator
Open Agent mode in chat and ask: "Using Tool Call Schema Validator, help me...". 3 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"tool-call-schema-validator": {
"url": "https://edge.vinkius.com/vk_preview_fjeQqEAkovq6wv5QOSR8yluR5fVJhGSyYuZMaIIw/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 Tool Call Schema Validator
Ask Copilot: "Using Tool Call Schema Validator, help me...". 3 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"tool-call-schema-validator": {
"url": "https://edge.vinkius.com/vk_preview_fjeQqEAkovq6wv5QOSR8yluR5fVJhGSyYuZMaIIw/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 Tool Call Schema Validator
Open Cascade and ask: "Using Tool Call Schema Validator, help me...". 3 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"tool-call-schema-validator": {
"url": "https://edge.vinkius.com/vk_preview_fjeQqEAkovq6wv5QOSR8yluR5fVJhGSyYuZMaIIw/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 Tool Call Schema Validator
Ask Cline: "Using Tool Call Schema Validator, help me...". 3 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add tool-call-schema-validator --transport http "https://edge.vinkius.com/vk_preview_fjeQqEAkovq6wv5QOSR8yluR5fVJhGSyYuZMaIIw/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 Tool Call Schema Validator
Ask Claude: "Using Tool Call Schema Validator, show me...". 3 tools are ready
Where the request belongs
Work Tool Call Schema Validator can move forward.
This is for developers and engineers building autonomous agents that interact with real-world APIs or databases where bad data causes system crashes.
AI Engineer
Validating that agent-generated payloads meet strict API specifications before execution.
Backend Developer
Protecting production services from malformed requests sent by non-deterministic LLMs.
Data Engineer
Ensuring incoming agentic data streams adhere to specific schema constraints for downstream processing.
Build the capability set
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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 Tool Call Schema Validator connected.
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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 Tool Call Schema Validator.
The practical details behind the request, access and result.
How can Capability Call Schema Validator prevent my agent from breaking my API?
It acts as a buffer that checks every argument an agent tries to send against your specific rules. If the agent tries to send invalid data, the MCP catches it before the call ever reaches your API.
Can Capability Call Schema Validator handle deeply nested JSON objects?
Yes. It is designed to perform recursive checks, meaning it can validate complex, multi-layered objects and arrays just as easily as simple key-value pairs.
What makes Capability Call Schema Validator better than manual checks?
It uses standard JSON Schema, which is much more robust and easier to maintain than writing custom validation logic for every single capability your agent uses.
How does Capability Call Schema Validator help with debugging?
It provides exact paths to errors. Instead of a generic error message, you get the specific location in your data, like args.settings.theme, so you know exactly what to fix.
Is Capability Call Schema Validator compatible with my existing workflows?
Yes, it is built on the open standard, so you can connect it to any MCP-compatible client like Claude, Cursor, or Windsurf to add validation to your agentic loops.
What does this capability validate?
It validates that LLM-generated arguments strictly match a provided JSON Schema, including types, required fields, and logical constraints like min/max values.
How are errors reported?
Errors are reported using precise path notation, such as args.items[0].id, so you know exactly which part of the input failed validation.
Can it handle nested objects?
Yes, the validator uses recursive traversal to ensure every level of a nested object or array is checked against the schema.
One connection away
Give your agent a direct line to Tool Call Schema Validator.
Connect Tool Call Schema Validator once. Keep it beside 6,100+ managed Connectors when the next task needs more.
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