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Live 30 Actions

AniList MCP Server
for AI Agents

Connect your AI agent to StackOne's AniList MCP server and give it 30 MCP tools out of the box. Auth, tool execution, and security all managed.

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AniList MCP Server
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30 Agent Actions

Agents can read, write, delete and run operations in AniList. Extend your agent's capabilities with custom actions.

Authentication

Agent Tool Authentication

Per-user OAuth in one call. Your AniList MCP server gets session-scoped tokens with zero credentials stored on your infra.

Agent Auth →

Security

Agent Protection

Every AniList tool response scanned for prompt injection in milliseconds, with 88.7% accuracy, all running on CPU.

Prompt Injection Defense →

Performance

Max Agent Context. Min Cost.

Free up to 96% of your agent's context window to enhance reasoning and reduce cost, on every AniList call.

Tools Discovery →

What is the AniList MCP Server?

A AniList MCP server lets AI agents read and write AniList data through the Model Context Protocol, Anthropic's open standard for connecting LLMs to external tools. StackOne's AniList MCP server ships with 30 pre-built actions, fully extensible via the Connector Builder, plus managed authentication, prompt injection defense, observability, and agent execution runtime. Connect it from MCP clients like Claude Desktop, Claude Code, Cursor, Goose, and VS Code, or from agent frameworks like OpenAI Agents SDK, LangChain, and Vercel AI SDK.

All AniList MCP Tools

Every StackOne action for AniList, ready for your agent. Read, write, delete and run operations, scoped to exactly what you need.

Characters

  • List Characters

    Search and list anime/manga characters.

  • Get Character

    Get a single character by id.

Medias

  • List Media

    Search and list anime or manga.

  • Get Media

    Get a single anime or manga by id.

Reviews

  • List Reviews

    List reviews written for anime and manga entries.

  • Get Review

    Get a single review by id.

  • Delete Review

    Permanently remove a review from a media entry.

Staffs

  • List Staff

    Search and list voice actors, directors and other production staff.

  • Get Staff

    Get a single staff member by id.

Studios

  • List Studios

    Search and list animation/production studios.

  • Get Studio

    Get a single studio by id.

Users

  • List Users

    Search and list AniList users.

  • Get User

    Get a single AniList user by id or name.

Other (17)

  • List Activity

    List social activity feed entries such as list updates and posts.

  • List Airing Schedule

    List upcoming and past episode airing times.

  • Get Media List Collection

    Get a user's full media list, grouped into status lists.

  • List Media List Entries

    List individual media list entries across users and media.

  • List Genre Collection

    List every genre name AniList uses to tag media.

  • List Media Tag Collection

    List every descriptive tag AniList uses to classify media.

  • List Notifications

    List the authenticated user's notifications.

  • List Recommendations

    List media-to-media recommendations submitted by users.

  • List Forum Threads

    Search and list AniList forum discussion threads.

  • Get Current User

    Get the profile of the authenticated user.

  • Delete Media List Entry

    Delete a media list entry.

  • Toggle Favourite

    Add or remove an anime, manga, character, staff or studio from favourites.

  • Save Media List Entry

    Create or update a media list entry for the authenticated user.

  • Save Recommendation

    Submit or update a recommendation linking two media entries together.

  • Save Review

    Create or update a review for a media entry.

  • Rate Review

    Upvote, downvote, or clear your vote on another user's review.

  • Toggle Follow User

    Follow or unfollow another user.

Set Up Your AniList MCP Server in Minutes

One endpoint. Any framework. Your agent is talking to AniList in under 10 lines of code.

Agent Frameworks

Claude Desktop
{
  "mcpServers": {
    "stackone": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote@latest",
        "https://api.stackone.com/mcp?x-account-id=<account_id>",
        "--header",
        "Authorization: Basic <YOUR_BASE64_TOKEN>"
      ]
    }
  }
}

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AniList MCP Server FAQ

Does StackOne have a AniList MCP server?
Yes. StackOne offers a hosted AniList MCP server with 30 pre-built actions, and every action is tested and QA'd by StackOne. Connect it to Claude, Cursor, and any other MCP client, or to any agent framework through the AI Action SDK. It ships with managed agent authentication, prompt injection defense, and tool discovery with server-side execution that preserve your agent's context window and keep reasoning performance.
AniList MCP server vs direct API integration: what's the difference?
A AniList MCP server and direct API integration serve different use cases. Direct API integration is for software-to-software work, where backend code calls AniList. A AniList MCP server is for AI agents that discover and call AniList at runtime, such as MCP clients like Claude and Cursor, plus framework agents built with OpenAI, LangChain, or Vercel AI. StackOne provides both.
How does AniList authentication work for AI agents?
AniList authentication for AI agents works through a StackOne Connect Session. Create one via the dashboard or the SDK to get an auth link and ready-to-paste config for Claude Desktop, Cursor, and other MCP clients. Your user authenticates their own AniList account; StackOne handles token exchange, storage, and refresh. Credentials never reach the LLM, and each user is isolated via origin_owner_id.
Are AniList MCP tools vulnerable to prompt injection?
Yes. AniList MCP tools can be vulnerable to indirect prompt injection. Any tool that reads user-written content, such as documents, messages, tickets, records, or free-text fields, is a potential vector. StackOne Defender scans every tool response before it enters the agent's context. It runs regex patterns in ~1ms, then a MiniLM classifier in ~4ms. Accuracy is 88.7%, and it runs entirely on CPU.
What is the context bloat of a AniList agent and how do I avoid it?
Context bloat happens when AniList tool schemas and API responses eat your AniList agent's memory, preventing it from reasoning effectively. A single AniList query can return a massive JSON response, and connecting multiple tools compounds the problem. Tools Discovery reduces it by loading only the tools relevant to each query.
Can I limit which actions my AniList agent can access?
Yes. You can limit which actions your AniList agent can access directly from the StackOne dashboard. Toggle actions on or off, or restrict them to specific accounts, with no code changes to your agent. Session tokens can be scoped to exact actions so if one leaks, exposure stays contained.
Can I create custom agent actions for my AniList MCP server?
Yes. You can create custom agent actions for your AniList MCP server using Connector Builder. It's an integration agent your coding assistant (Claude Code, Cursor, or Copilot) can invoke to research AniList's API, generate production-ready connector YAML, test against the live API, and validate before you ship.
When should I NOT use a AniList MCP server?
Skip a AniList MCP server if your integration is purely software-to-software, because direct AniList API integration is simpler when no AI agent is involved. For deterministic, compliance-critical operations (financial transactions, regulatory reporting), direct API gives you predictable behavior without agent-driven decision-making. MCP shines when AI agents need to dynamically discover and call AniList actions at runtime.
What AI frameworks and AI clients does the StackOne AniList MCP server support?
The StackOne AniList MCP server supports both. MCP clients (paste-and-go apps): Claude Desktop, Claude Code, Cursor, VS Code, Goose. Agent frameworks (code SDKs you build with): OpenAI Agents SDK, Anthropic, Vercel AI, Google ADK, CrewAI, Pydantic AI, LangChain, LangGraph, Azure AI Foundry.

Put your AI agents to work

All the tools you need to build and scale AI agent integrations, with best-in-class connectivity, execution, and security.