How to Use the AniList GraphQL MCP in AutoGen

Q: How do I register AniList GraphQL MCP tools with my AutoGen agents?

You use the mcpservertools helper with your Vinkius HTTP URL to fetch the tool definitions. Pass this list to your AssistantAgent constructor, and the framework automatically maps the schemas for tools like searchmedia.

Q: How does AutoGen handle the schema format of the AniList GraphQL tools?

The McpToolAdapter handles the conversion automatically. It translates the server's input schemas into the format that your agents expect, so they can call savemedialistentry without manual formatting.

Let your AutoGen agents debate and coordinate to manage your AniList GraphQL watchlists and favorites.

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Connect AniList GraphQL MCP to AutoGen

Create your Vinkius account to connect AniList GraphQL to AutoGen 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 AutoGen

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Let AutoGen agents debate seasonal anime picks

The `get_media` tool provides the raw anime data for your AutoGen agents to analyze and discuss. One agent can review the studio history using `get_studio` while another checks user ratings to debate if a show is worth adding. Once they agree, a list-manager AutoGen agent calls `save_media_list_entry` to update your AniList profile. This multi-agent setup ensures only high-quality recommendations make it onto your watchlist.

Coordinate profile updates across an MCP Server

The `get_viewer` tool lets your AutoGen agents audit your current AniList profile settings and lists. If they detect inconsistencies, they coordinate to clean up your entries. A specialized AutoGen agent can run `delete_media_list_entry` to prune dropped anime, while another uses `toggle_follow` to manage your social connections. They work in parallel, keeping your profile organized.

Analyze anime creators with specialized research agents

The `get_character` and `search_staff` tools feed your AutoGen research team detailed anime profiles. One agent can focus on tracking down voice actors while another analyzes the characters they play. They share this information in the AutoGen group chat to build a detailed report on an anime's creative team. If they find a standout creator, they call `toggle_favourite` to save them to your profile.

Setup guide

Set up AniList GraphQL MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes AniList GraphQL tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="AniList GraphQL_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent AniList GraphQL data")
print(result.messages[-1].content)

Get your connection token →

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="AniList GraphQL_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent AniList GraphQL data")
    print(result.messages[-1].content)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by AniList. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about AniList GraphQL MCP in AutoGen

You use the `mcp_server_tools` helper with your Vinkius HTTP URL to fetch the tool definitions. Pass this list to your `AssistantAgent` constructor, and the framework automatically maps the schemas for tools like `search_media`.

Yes, they share the same tool definitions. A research agent can call `get_character` while a social agent calls `toggle_follow` in the same conversation thread, allowing coordinated actions.

The `McpToolAdapter` handles the conversion automatically. It translates the server's input schemas into the format that your agents expect, so they can call `save_media_list_entry` without manual formatting.

Yes, you can run a command-line agent that prompts you for confirmation before executing mutating actions like deleting a list entry.

Yes, your personal list data and authentication tokens are processed entirely in memory within an ephemeral V8 sandbox. Vinkius never writes this data to disk, keeping your account credentials and viewing habits secure.

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