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naipi11
by naipi11

Related Servers

Alternatives to workbuddy-gpt-image

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    Related Servers

    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables MCP clients to generate images, edit existing ones, and create matching image sets using either the Codex CLI or the OpenAI Images API. It returns previews and saved file paths so agents can inspect results and continue iterating.
      MIT
    • A
      license
      A
      quality
      B
      maintenance
      Enables MCP-compatible coding agents to generate and edit images from text prompts or local files, returning both a saved file path and an inline image block. Supports up to four sequential images per call, model listing, and one-command setup across OMP, Codex, Claude Code, Cursor, and opencode.
      3
      0
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Exposes Codex's built-in image generation to any MCP-capable agent, returning file paths, pixel dimensions, and the prompts used, with support for image-to-image editing via reference images. Ships scenario presets (Xiaohongshu, video cover, poster, book/album cover and more) plus built-in prompt assembly and catalog listing tools so agents can generate or preview prompts without spending credits.
      136
      MIT

    TDQS

    A4.1/5.0

    Scored across 4 tools

    Disambiguation5/5

    Each tool targets a distinct lifecycle stage: submit (generate_gpt_image), poll/wait (get_image_job), cancel (cancel_image_job), and backend health (check_image_backend). The descriptions explicitly contrast them, e.g. check_image_backend notes it does not generate while generate_gpt_image warns you must poll with get_image_job.

    Naming Consistency5/5

    All four names use strict snake_case with a clear verb_noun form (get_image_job, cancel_image_job, generate_gpt_image, check_image_backend). Consistent convention throughout with shared _image_job / _image_backend suffixes reinforcing grouping.

    Tool Count5/5

    Four tools map cleanly onto the async image-generation lifecycle with no filler. This is a well-scoped, focused surface for a single-domain server.

    Completeness4/5

    Submit, poll, cancel, and backend-check cover the core async lifecycle, and the descriptions make the intended flow clear. Minor gap: no list-jobs or result-retrieval/cleanup operation, so an agent tracking multiple jobs has no enumeration tool.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues