How to Use the AniList GraphQL MCP in OpenAI Agents SDK

Manage your anime watchlists directly through your OpenAI Agents SDK production pipeline.

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Connect AniList GraphQL MCP to OpenAI Agents SDK

Create your Vinkius account to connect AniList GraphQL to OpenAI Agents SDK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup AniList GraphQL with OpenAI Agents SDK

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Full database access for OpenAI Agents SDK

Your agent queries the AniList catalog to pull metadata on demand. It uses `get_media` and `get_character` to verify plot details or cast info before your agent makes a decision. Everything happens inside your existing Python agent flow. The SDK handles the tool discovery so your code stays clean and focused on your business logic.

Update your lists via OpenAI Agents SDK

Trigger `save_media_list_entry` when your agent determines a user finished a series. This keeps your external watchlists perfectly synced with your agent's state. It handles the heavy lifting of state management. You just pass the command and the MCP server ensures your data hits the database correctly.

Control favorites with OpenAI Agents SDK

Call `toggle_favourite` to let your agent curate user preferences automatically. It reacts to conversational context to mark specific studios or staff as high priority. This creates a direct feedback loop between your user and their preferences. The SDK keeps the connection stable while your agent manages the interaction.

Setup guide

Set up AniList GraphQL MCP in OpenAI Agents SDK

Prerequisites

Python 3.10+ installed
openai-agents package (pip install openai-agents)
Active Vinkius subscription with a valid endpoint token

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all AniList GraphQL tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives AniList GraphQL tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate AniList GraphQL tools and returns structured results. Copy the full example on the right to get started.

agent.py

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="AniList GraphQL Agent",
            instructions="You have access to AniList GraphQL tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Common questions about AniList GraphQL MCP in OpenAI Agents SDK

Connect the server via MCPServerStreamableHttp in your agent constructor. Your agent will automatically discover all 15 tools and map them to its execution path.

Yes, the SDK maps the GraphQL schema directly to the tools provided. Your agent handles the serialized data returned by the server without extra parsing.

Your agent only transmits the data required for specific tool calls. Access is limited to your authenticated session token, keeping your private watchlists isolated.

You just need the endpoint URL and your auth token. The SDK handles the transport layer so you can focus on building your agent's logic.

Your credentials never touch the model. They stay inside the Vinkius sandbox, and the server signs your requests so your data remains strictly between you and the API.

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