vision-mcp
Related Servers
Alternatives to vision-mcp
No user-submitted related servers found.
Related Servers
- AlicenseAqualityAmaintenanceGives text-only LLM coding agents vision by routing images to a multimodal model and returning detailed textual descriptions. Supports local files, URLs, clipboard, base64, raw bytes, and multiple providers like OpenAI, Anthropic, and Gemini.182 npm13MIT
- AlicenseAqualityCmaintenanceGives text-only coding agents the ability to 'see' images, videos, and screenshots by routing them to a vision model and returning structured text.815 npm1MIT
- AlicenseAqualityDmaintenanceEnables AI agents to analyze images, extract text, compare images, and analyze video through any OpenAI-compatible vision model.4151 npm20MIT
- AlicenseNot gradedqualityAmaintenanceEnables text-only AI agents to see images on demand by calling any OpenAI-compatible vision API for OCR, image analysis, structured extraction, image comparison, and GUI screenshot-to-accessibility-tree conversion.1MIT
- AlicenseAqualityAmaintenanceEnables text-only coding agents to analyze local images using a dedicated vision provider, returning markdown and structured JSON evidence for screenshots, diagrams, UI mockups, and error captures.1190 npm10MIT
- AlicenseAqualityBmaintenanceEnables AI agents to analyze images via user-configured cloud vision APIs (Gemini or OpenAI-compatible), returning structured results such as summaries, OCR text, and objects.41MIT
TDQS
Scored across 2 tools
The two tools are clearly separated by media type: images versus videos. An agent can easily select the right tool based on the file extension or input format, with no meaningful overlap.
Both tools follow the exact same verb_noun snake_case pattern: analyze_image and analyze_video. The naming is clean, predictable, and immediately signals what each tool does.
Two tools is minimal but reasonable for a vision server focused on content description of static and moving media. Each tool earns its place, though the set feels slightly thin compared to broader vision-capable servers.
The core workflow of analyzing visual media is covered: images and videos both have a dedicated tool. Minor gaps exist, such as no URL-based input and no specialized vision capabilities like OCR or object detection, but these are not clearly implied by the server's stated scope.