Output Format Contract Checker Connector for AI agents.
3 live capabilities
Enforce strict data schemas for reliable agentic workflows
Waiting for input…
Why people use Output Format Contract Checker
Stop LLM output errors with Output Format Contract Checker
This MCP changes that by acting as a structural firewall. Instead of waiting for your code to throw an exception, you get an immediate, clear signal when the data doesn't match your requirements. You get a clean, actionable report that tells you exactly what went wrong, so you can fix your prompts or your code immediately.
What Vinkius changes
That it stops broken data from crashing your automated workflows.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 6,100+ Connectors
- Real-world use case 01
Preventing JSON parsing errors in LangChain
An agent produces a conversational response instead of a JSON object, causing a crash.
- Real-world use case 02
Ensuring consistent data for database ingestion
An agent extracts user info, but misses a required field.
- Real-world use case 03
Validating multi-step CrewAI tasks
A researcher agent passes data to a writer agent.
Complete set · 3capabilities
The complete Output Format Contract Checker capability set.
These are the exact actions your AI can choose when you ask it to work with Output Format Contract Checker.
01—03
3 capabilities in this set.
Part of 3 available through Output Format Contract Checker.
- 01 Capability
Check coercion possibility
Checks if a value can be converted to the required type. It helps determine if a mismatch is a fatal error or a simple fix.
- 02 Capability
Get violation summary
Groups all detected errors into a single summary. This makes it easy to see exactly how many fields failed validation.
- 03 Capability
Validate contract
Checks if the provided data matches your specific schema requirements. It catches missing fields and incorrect types instantly.
Set up in minutes
One URL. Then ask Output Format Contract Checker to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Output Format Contract Checker 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_sz61NzRUL9NbAEZD1qWtKAZjz9dZSg1OIgnAzCiK/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 Output Format Contract Checker, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable Output Format Contract Checker for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_sz61NzRUL9NbAEZD1qWtKAZjz9dZSg1OIgnAzCiK/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 Output Format Contract Checker URL.
- Step 03
Save and start
Save the connection and enable Output Format Contract Checker in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"output-format-contract-checker": {
"url": "https://edge.vinkius.com/vk_preview_sz61NzRUL9NbAEZD1qWtKAZjz9dZSg1OIgnAzCiK/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 Output Format Contract Checker
Open Agent mode in chat and ask: "Using Output Format Contract Checker, help me...". 3 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"output-format-contract-checker": {
"url": "https://edge.vinkius.com/vk_preview_sz61NzRUL9NbAEZD1qWtKAZjz9dZSg1OIgnAzCiK/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 Output Format Contract Checker
Ask Copilot: "Using Output Format Contract Checker, help me...". 3 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"output-format-contract-checker": {
"url": "https://edge.vinkius.com/vk_preview_sz61NzRUL9NbAEZD1qWtKAZjz9dZSg1OIgnAzCiK/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 Output Format Contract Checker
Open Cascade and ask: "Using Output Format Contract Checker, help me...". 3 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"output-format-contract-checker": {
"url": "https://edge.vinkius.com/vk_preview_sz61NzRUL9NbAEZD1qWtKAZjz9dZSg1OIgnAzCiK/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 Output Format Contract Checker
Ask Cline: "Using Output Format Contract Checker, help me...". 3 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add output-format-contract-checker --transport http "https://edge.vinkius.com/vk_preview_sz61NzRUL9NbAEZD1qWtKAZjz9dZSg1OIgnAzCiK/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 Output Format Contract Checker
Ask Claude: "Using Output Format Contract Checker, show me...". 3 tools are ready
Where the request belongs
Work Output Format Contract Checker can move forward.
This is for engineers and developers building multi-step agentic workflows who are tired of their pipelines breaking because an LLM decided to be creative with its formatting.
AI Engineer
Validating that agent outputs match the JSON schemas required by downstream microservices.
LLM Ops Engineer
Monitoring pipeline health and ensuring data integrity across large-scale agent deployments.
Data Engineer
Ensuring structured data extracted by agents remains consistent for database ingestion.
Build the capability set
Add more capabilities.
Each Connector adds new actions and data without changing how you work.
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Deterministic parser and validator for vCard (VCF) strings.
Constraint Satisfaction Verifier
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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 Output Format Contract Checker 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 Output Format Contract Checker.
The practical details behind the request, access and result.
How does Output Format Contract Checker prevent pipeline failures?
It intercepts agent outputs and verifies they match your required schema. By catching type mismatches or missing fields early, it prevents these errors from crashing your downstream applications.
Can I use Output Format Contract Checker with any agent framework?
Yes. It works with any agentic workflow, including those built with LangChain or CrewAI, as long as you can pass the output to this MCP for validation.
Does Output Format Contract Checker help with fixing data errors?
It helps identify if errors are fixable. It can tell you if a value can be coerced into the correct type, making it easier to automate the correction process.
What kind of errors does Output Format Contract Checker catch?
It catches missing required fields, incorrect data types, invalid enum values, and nullability violations that don't match your defined schema.
Is Output Format Contract Checker useful for production AI apps?
Absolutely. It provides the structural reliability needed to move AI agents from experimental scripts to stable, production-ready software systems.
What does this MCP do?
It validates that JSON data produced by an AI agent matches a specific schema, checking for missing fields, type mismatches, and enum violations using validate_contract.
Can it fix schema errors automatically?
It identifies if errors are fixable via check_coercion_possibility, which checks for simple type conversions like string to integer.
How do I see a summary of all errors?
You can use the get_violation_summary capability to get a categorized report of all detected contract breaches.
One connection away
Give your agent a direct line to Output Format Contract Checker.
Connect Output Format Contract Checker once. Keep it beside 6,100+ managed Connectors when the next task needs more.
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