Vignetim OpenAI MCP

Prijunkite Vignetim partnerių API prie Cursor, Windsurf, Continue, OpenAI Agents SDK ir bet kurios platformos, palaikančios Model Context Protocol.

Greitas nustatymas

Cursor

Atidarykite 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

Pridėkite prie savo Windsurf MCP konfigūracijos:

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

Continue (VS Code)

Pridėkite prie .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');

Galimi įrankiai (iš viso 19)

Produktai (6 įrankiai)

Užsakymai (4 įrankiai)

Webhooks (5 įrankiai)

Dokumentacija (4 įrankiai — autentifikacija nereikalinga)

Individualaus agento kūrimas

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 režimas

Pridėkite X-Environment: sandbox prie savo antraščių, kad naudotumėte sandbox API su imituojamais mokėjimais:

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

Alternatyva: tiesioginė HTTP prieiga

Jei jūsų platforma nepalaiko MCP:

Trikčių šalinimas

„API credentials required"

API įrankiams reikia abiejų X-API-Key ir X-API-Secret antraščių. Dokumentacijos įrankiai veikia be kredencialų.

Ryšio problemos

Patikrinkite, ar galinis taškas pasiekiamas:

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

Užklausų ribojimas

MCP serveris laikosi partnerių API užklausų limitų: 100 užkl./min bendrai, 10 užkl./min užsakymų kūrimui. Sandbox turi 5x daugiklį.