AniList MCP Server is a powerful tool that connects AI models to the vast AniList database, providing access to comprehensive anime, manga, character, and staff data. As an MCP server, it empowers AI agents to search for media, retrieve detailed information, and even access user profiles, significantly enhancing their understanding of anime and manga culture.

This solution addresses the challenge of integrating real-time, structured anime and manga data into AI workflows. By offering a suite of tools for searching, retrieving, and even interacting with AniList data (like favoriting entries), it enables developers to build AI applications with a deep understanding of the anime and manga landscape. The server seamlessly integrates with AI models through standard MCP protocols, using tools like mcp-get or Smithery for easy installation. It supports features requiring user authentication via an optional AniList API token, making it a versatile asset for any AI project involving anime or manga.

Access AniList's Rich Media Data

The AniList MCP server provides a comprehensive interface to the AniList API, granting AI models access to a vast database of anime, manga, characters, and staff information. This includes detailed descriptions, ratings, reviews, and relationships between different media. By leveraging this data, AI models can gain a deeper understanding of the anime and manga landscape, enabling them to provide more informed and nuanced responses to user queries. For example, an AI could use this tool to answer questions like "What are some anime similar to 'Attack on Titan'?" or "Who is the voice actor for Levi Ackerman?". This access empowers AI to deliver accurate and context-aware information, enhancing user engagement and satisfaction.

Technically, the server uses the AniList GraphQL API to fetch data, and exposes different tools for different types of queries.

Personalized Recommendations and Insights

Beyond basic data retrieval, the AniList MCP server allows AI models to access user-specific data, such as anime and manga lists, and personalized recommendations. This enables AI to provide tailored suggestions and insights based on individual preferences. For instance, an AI could analyze a user's watch history and recommend similar anime they might enjoy, or provide personalized summaries of ongoing series based on their viewing progress. This level of personalization enhances the user experience by making the interaction with the AI more relevant and engaging. Accessing user data requires authentication via an AniList API token.

The server implements tools like get_user_anime_list, get_recommendations_for_media and requires the ANILIST_TOKEN environment variable to be set for authenticated requests.

Dynamic Content Creation and Interaction

The AniList MCP server empowers AI models to not only access information but also interact with the AniList platform on behalf of the user. This includes functionalities like adding entries to a user's anime or manga list, posting activity updates, and even favoriting characters or staff members. This opens up possibilities for AI-driven content creation and community engagement. For example, an AI could automatically update a user's anime list as they watch new episodes, or generate personalized recommendations based on trending discussions on the platform. This dynamic interaction fosters a more immersive and engaging experience for users.

These interactive features are implemented through tools like add_list_entry, post_text_activity, and favourite_character, all of which require user authentication via the ANILIST_TOKEN.