LLM & MCP Integration

Connect AI coding tools to Yuno’s payment APIs using Model Context Protocol (MCP)

Public Beta. MCP integration uses the open Model Context Protocol standard. Connect any MCP-compatible AI tool to Yuno’s API. Available for all plan tiers in sandbox; production access requires account approval.

Credentials: MCP env vars and REST headers

The MCP server reads environment variables. When you call Yuno REST APIs directly (or read curl in the docs), use HTTP headers with these exact names:

MCP / server env (typical)	REST header on api.y.uno / api-sandbox.y.uno
YUNO_PUBLIC_KEY	public-api-key
YUNO_PRIVATE_KEY	private-secret-key
YUNO_ACCOUNT_CODE	account_id

See also AI agents compatibility for the full read order for tools indexing this repo.

Overview

Yuno supports the Model Context Protocol (MCP) to enable AI-powered development tools (like Claude Code, Cursor, and Windsurf) to interact directly with Yuno’s payment APIs. This integration allows AI assistants to query payment data, create test transactions, and debug integration issues using natural language.

MCP integration is designed for development and debugging workflows. It should not be used for production payment processing.

What is MCP?

Model Context Protocol (MCP) is an open standard that allows AI applications to connect to external data sources and tools. Yuno’s MCP server exposes payment API capabilities as MCP tools that AI assistants can invoke.

Available MCP Tools

Tool	Description	Use Case
create_checkout_session	Create a new checkout session	Start a payment flow
create_payment	Create a payment	Test payment creation
get_payment	Retrieve payment details	Debug payment status
list_payments	List recent payments	Review transaction history
create_refund	Process a refund	Test refund flows
get_payment_methods	List available methods	Check method availability
validate_payload	Validate a payment payload	Pre-flight validation

Setting Up MCP Integration

1. Install the Yuno MCP server

   Install the Yuno MCP server package:

   npm install -g @yuno-payments/mcp-server
   

   Or use npx for a one-time run:

   npx @yuno-payments/mcp-server
   
2. Configure credentials

   Set your Yuno sandbox credentials as environment variables:

   export YUNO_PUBLIC_KEY="your-sandbox-public-key"
   export YUNO_PRIVATE_KEY="your-sandbox-private-key"
   export YUNO_ACCOUNT_CODE="your-sandbox-account-id"
   export YUNO_ENVIRONMENT="sandbox"
   

   Only use sandbox credentials with MCP. Never configure production credentials in AI development tools.

3. Connect to your AI tool

   Configure your AI tool to use the Yuno MCP server. See Remote MCP Server Setup for tool-specific configuration.

Usage Examples

Natural Language Queries

Once connected, you can interact with Yuno through natural language:

• “Create a checkout session for $50 USD in Colombia”
• “Show me the last 10 failed payments”
• “What payment methods are available for Brazil?”
• “Validate this payment payload for PIX”
• “Get the details of payment pay_abc123”

AI-Assisted Debugging

Use MCP to debug integration issues directly in your IDE:

Developer: "I'm getting a 400 error when creating a PIX payment.
Can you validate my payload?"

AI Assistant: [Calls validate_payload tool]
"Your payload is missing the customer.document field.
PIX requires a CPF or CNPJ for Brazilian transactions.
Here's the corrected payload: ..."

Supported AI Tools

Tool	MCP Support	Configuration
Claude Code	Native	.claude/settings.json
Cursor	Via extension	Settings > MCP
Windsurf	Via extension	Settings > MCP
VS Code + Continue	Via extension	.continue/config.json

Security Considerations

• MCP tools run in your local environment with your credentials
• All API calls go through the standard Yuno API with your sandbox keys
• No payment data is sent to the AI model’s training pipeline
• Use sandbox credentials exclusively for MCP integrations
• Rotate credentials if they are accidentally exposed

Rate Limits

MCP tool calls count against your standard API rate limits. The sandbox has more lenient limits, but avoid excessive automated queries.