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Related Servers

Alternatives to SayMaker MCP

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    Related Servers

    • A
      license
      Not graded
      quality
      A
      maintenance
      Exposes over 70 generation and editing tools for images, video, audio, PDFs, and 3D assets to any MCP-compatible client, with async job polling, saved-media libraries, and credit tracking. Users can produce product shots, voiceovers, subtitles, and more without leaving their chat client.
      35 npm
      1
      MIT
    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables generating and editing images from any MCP client by expanding short requests into detailed visual prompts, then saving the results to disk and returning them as resources. Supports Gemini, OpenAI GPT Image, and BytePlus Seedream with quality presets, aspect ratios, up to 4K output, and options for character consistency and Google Search grounding.
      1,984 npm
      MIT
    • A
      license
      Not graded
      quality
      D
      maintenance
      Enables AI image and video generation using Dreamshot's API, supporting tools like image editing, video creation, and enhancement directly from MCP-compatible clients.
      MIT

    TDQS

    A3.9/5.0

    Scored across 6 tools

    Disambiguation5/5

    Each tool targets a clearly distinct operation: generating an image, generating a video, editing an existing image, listing models, polling a task, and opening the web app. The only potential overlap is generate_video with an image_url versus edit_image, but the descriptions make the output modality and intent clear.

    Naming Consistency5/5

    All tool names follow a consistent lowercase verb_noun pattern: edit_image, list_models, generate_image, generate_video, get_task, open_in_saymaker. The naming is predictable and makes the action and target resource immediately understandable.

    Tool Count5/5

    Six tools is well-scoped for an image and video generation service. Each tool covers a necessary part of the workflow without redundant or filler operations.

    Completeness4/5

    The core lifecycle is covered: list available models, generate an image, edit an image, generate a video, poll for results, and continue in the browser. Minor gaps like an explicit cancel-task or credit-balance tool are absent, but agents can still complete the primary workflows.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues