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Alternatives to Image Forge

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    Related Servers

    • 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
      Enables coding agents and other MCP clients to generate images from text prompts and edit, restyle, or extend existing images through an OpenAI-compatible /v1/images API. Results are returned both inline as image content blocks and as files saved to disk, so agents can view and reuse them within a normal task.
      25 npm
      1
      MIT
    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables generating and editing images with OpenAI's gpt-image-2 directly from Claude or ChatGPT, including uploads, masks, composition, listing, deletion, and spend tracking through a self-hosted Cloudflare Workers connector.
      MIT

    TDQS

    A3.7/5.0

    Scored across 3 tools

    Disambiguation5/5

    Each tool targets a clearly distinct operation: text-to-image (generate_image), image+prompt-to-image (edit_image), and local metadata inspection (get_image_info). There is no plausible overlap; the descriptions explicitly contrast the source of input (text vs. existing image) and note that get_image_info consumes no API quota, further separating it.

    Naming Consistency5/5

    All three names follow a strict verb_noun snake_case pattern (edit_image, generate_image, get_image_info), with verbs that accurately match the action. No camelCase mixing or vague verbs.

    Tool Count4/5

    Three tools is a small but coherent surface for an image generation server — one per core action (generate, edit, inspect). It is slightly thin (no listing, batch, or transform operations), but nothing feels redundant or unearned.

    Completeness3/5

    The generate/edit/inspect cycle covers the primary workflow, but common adjacent operations are absent: resize/crop/convert, upscaling or variations, inpainting with masks, and any way to list or clean up previously written files. An agent can produce and inspect images but hits dead ends for post-processing or asset management.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues