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"Servers Offering MCP Prompts as Prompt Primitives" matching MCP servers:

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    Mercury Spec Ops MCP Server is a dynamic prompt generation and template assembly tool based on a modular architecture. It is suitable for the interaction between AI assistants and professional content, and supports the dynamic generation of 31 technology stacks, 10 analysis dimensions and 34 templat
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    Apache 2.0
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    Generates creative illustration prompts featuring characters from the Love Live! franchise (μ's, Aqours, Nijigasaki, Liella!, Hasunosora, and Ikizurai) with randomized settings including characters, locations, times, actions, and items.
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    An MCP server for the Servarr stack — Sonarr, Radarr, Lidarr, Readarr, and Prowlarr — packaged as a Docker container. Lets an MCP client (Claude Desktop, etc.) browse and search whichever \*arr apps you're running.
    29
    MIT
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    Exposes Spotify controls as MCP tools for playback, playlist management, and AI playlist generation; includes a web app and supports multi-user profiles.
    14
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    MCP server that exposes Mylar3's HTTP API as tools, letting an LLM read and manage a comic library including watchlist, wanted issues, upcoming, history, logs, story arcs, and providers.
    5
    MIT
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    The Atlas Docs MCP server provides technical documentation of libraries and frameworks for AI assistants, processes the official documentation into Markdown versions suitable for LLMS, and is applicable to McP-compatible LLM clients such as Cursor, Cline, Windsurf, etc.
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    Apache 2.0
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    MCP server exposing Tracearr's Public API v2 as read-only tools to query Plex, Jellyfin, and Emby monitoring data such as watch history, active streams, media, users, libraries, and recently added items.
    13
    MIT
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    Exposes a user's MyAnimeList data (watch list, scores, statistics) as MCP tools for AI assistants to analyze taste, build statistics, and make recommendations.
    20
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    MIT
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    A smart AniList integration for the Model Context Protocol that provides AI assistants with tools for searching media, managing watchlists, and analyzing user anime or manga tastes. It goes beyond basic API calls by offering personalized recommendations, taste comparisons, and natural language profile summaries.
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    MIT