Vignetim OpenAI MCP

Connect the Vignetim Partner API to Cursor, Windsurf, Continue, OpenAI Agents SDK, and any platform supporting the Model Context Protocol.

Quick Setup

Cursor

Open Cursor Settings → MCP → Add new MCP server:

{
	"mcpServers": {
		"vignetim": {
			"url": "https://vignetim.com/api/mcp",
			"headers": {
				"X-API-Key": "YOUR_API_KEY",
				"X-API-Secret": "YOUR_API_SECRET"
			}
		}
	}
}

Windsurf

Add to your Windsurf MCP configuration:

{
	"mcpServers": {
		"vignetim": {
			"serverUrl": "https://vignetim.com/api/mcp",
			"headers": {
				"X-API-Key": "YOUR_API_KEY",
				"X-API-Secret": "YOUR_API_SECRET"
			}
		}
	}
}

Continue (VS Code)

Add to .continue/config.json:

{
	"mcpServers": [
		{
			"name": "vignetim",
			"url": "https://vignetim.com/api/mcp",
			"headers": {
				"X-API-Key": "YOUR_API_KEY",
				"X-API-Secret": "YOUR_API_SECRET"
			}
		}
	]
}

OpenAI Agents SDK (Python)

from openai_agents import Agent, MCPServerStreamableHttp

async with MCPServerStreamableHttp(
    url="https://vignetim.com/api/mcp",
    name="vignetim",
    headers={
        "X-API-Key": "YOUR_API_KEY",
        "X-API-Secret": "YOUR_API_SECRET",
    },
) as mcp:
    agent = Agent(
        name="Vignetim Partner",
        instructions="You manage Vignetim API integration. Browse products, create orders, and manage webhooks.",
        mcp_servers=[mcp],
    )
    result = await agent.run("List all Hungarian vignettes for cars")

OpenAI Agents SDK (Node.js)

import { Agent, MCPServerStreamableHttp } from '@openai/agents';

const mcp = new MCPServerStreamableHttp({
	url: 'https://vignetim.com/api/mcp',
	name: 'vignetim',
	headers: {
		'X-API-Key': 'YOUR_API_KEY',
		'X-API-Secret': 'YOUR_API_SECRET',
	},
});

await mcp.connect();

const agent = new Agent({
	name: 'Vignetim Partner',
	instructions: 'You manage Vignetim API integration.',
	mcpServers: [mcp],
});

const result = await agent.run('Show me my recent orders');

Available Tools (19 total)

Products (6 tools)

Orders (4 tools)

Webhooks (5 tools)

Documentation (4 tools — no auth required)

Building a Custom Agent

from openai_agents import Agent, MCPServerStreamableHttp, Runner

SYSTEM_PROMPT = """You are a Vignetim Partner API assistant.
You help manage e-vignette, eSIM, and insurance orders.

Available actions:
- Browse products (vignettes, eSIM packages, insurance)
- Create and track orders
- Set up and manage webhook notifications
- Search API documentation for integration help

Always confirm before creating orders or modifying webhooks.
Use sandbox mode for testing."""

async def main():
    async with MCPServerStreamableHttp(
        url="https://vignetim.com/api/mcp",
        name="vignetim",
        headers={
            "X-API-Key": "YOUR_KEY",
            "X-API-Secret": "YOUR_SECRET",
            "X-Environment": "sandbox",
        },
    ) as mcp:
        agent = Agent(
            name="Vignetim Assistant",
            instructions=SYSTEM_PROMPT,
            mcp_servers=[mcp],
        )
        result = await Runner.run(
            agent,
            "Set up webhooks for order.completed and order.failed events "
            "at https://myapp.com/api/webhooks/vignetim, then send a test event."
        )
        print(result.final_output)

Sandbox Mode

Add X-Environment: sandbox to your headers to use the sandbox API with simulated payments:

{
	"headers": {
		"X-API-Key": "YOUR_SANDBOX_KEY",
		"X-API-Secret": "YOUR_SANDBOX_SECRET",
		"X-Environment": "sandbox"
	}
}

Alternative: Direct HTTP Access

If your platform doesn't support MCP:

Troubleshooting

"API credentials required"

API tools need both X-API-Key and X-API-Secret headers. Documentation tools work without credentials.

Connection Issues

Verify the endpoint is reachable:

curl -X POST https://vignetim.com/api/mcp \
  -H "Content-Type: application/json" \
  -d '{"jsonrpc":"2.0","id":1,"method":"tools/list","params":{}}'

Rate Limiting

The MCP server respects Partner API rate limits: 100 req/min general, 10 req/min for order creation. Sandbox has a 5x multiplier.