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Related Servers

Alternatives to UNO-MCP

No user-submitted related servers found.

    Related Servers

    • A
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      Combines structured sequential thinking with batch operation execution, enabling step-by-step reasoning with revision/branching capabilities and chained operations with variable piping between steps.
      15
      1
      MIT
    • A
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      A narrative graph engine that enables LLMs to generate, track, and mutate complex fictional worlds while maintaining consistency between factions, characters, and locations. It acts as a specialized RAG framework for storytelling, allowing models to manage thousands of entities without exceeding context limits.
      MIT
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      Enables AI-guided hierarchical fiction writing through structured XML documents. Supports step-by-step narrative expansion from book-level planning down to individual paragraphs, with custom Roo Code modes for collaborative story development.
      19
      MIT
    • A
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      Provides 30+ unified reasoning operations including systematic thinking, mental models, debugging approaches, statistical analysis, interactive notebooks, and advanced problem-solving frameworks for enhanced decision-making and complex reasoning tasks.
      96 npm
      53
      MIT
    • A
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      Enables iterative deep research by integrating AI agents with search engines, web scraping, and large language models for efficient data gathering and comprehensive reporting.
      4 npm
      323
      MIT

    TDQS

    C2.7/5.0

    Scored across 3 tools

    Disambiguation2/5

    The tools 'custom_enhance_text' and 'enhance_text' have overlapping purposes, both focused on enhancing story pages, with only a vague distinction based on technique selection versus using all techniques. This creates ambiguity where an agent might struggle to choose between them for a given enhancement task. The 'analyze_text' tool is more distinct but the enhancement tools lack clear boundaries.

    Naming Consistency4/5

    All tools follow a consistent snake_case naming pattern with a verb_noun structure (e.g., analyze_text, enhance_text). The naming is predictable and readable, with only minor deviation in 'custom_enhance_text' where the adjective 'custom' adds some variation but maintains the overall convention.

    Tool Count3/5

    With only 3 tools, the server feels thin for a domain like story analysis and enhancement, potentially lacking coverage for broader operations. While it covers basic analyze and enhance functions, the low count may limit agent capabilities in handling more complex workflows or additional CRUD-like actions.

    Completeness2/5

    The tool set is severely incomplete for a story analysis and enhancement domain, as it only includes analysis and enhancement without any CRUD operations (e.g., create, update, delete story pages) or lifecycle management. This creates significant gaps that will likely cause agent failures when trying to perform full workflows beyond simple text processing.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues