deepseek-vision-mcp
Related Servers
Alternatives to deepseek-vision-mcp
No user-submitted related servers found.
Related Servers
- FlicenseNot gradedqualityCmaintenanceMCP server that gives text-only models vision capabilities via free GLM vision models, supporting image description, OCR, chart/document analysis, and grounding with automatic model fallback.1-
- AlicenseNot gradedqualityBmaintenanceMCP server that gives text-only LLMs vision capabilities by using a free multimodal model to perceive images, audio, and video, returning text for the main model to reason with.39 npm1MIT
- FlicenseNot gradedqualityCmaintenanceAn MCP server that leverages Zhipu's free GLM-4.6V-Flash vision model to enable image, video, and file understanding (OCR, table parsing, defect detection, document Q&A, and more) across MCP-compatible clients like Codex and Claude Desktop.-
- FlicenseAqualityBmaintenanceA Model Context Protocol server that wraps the free GLM-4.6V-Flash vision model, enabling text-only LLM clients like Codex, Cursor, and Claude Desktop to analyze images, videos, and files (PDF/TXT) through standard MCP tools.32-
- AlicenseNot gradedqualityBmaintenanceMCP server that gives text-only LLMs like DeepSeek vision capabilities by converting images to text via vision APIs, enabling image description, OCR, and generation in MCP clients.1MIT
- AlicenseAqualityAmaintenanceMulti-model vision understanding MCP server that provides unified image analysis for AI assistants without native vision, supporting models like GLM-4.6V, DeepSeek-OCR, Qwen3-VL-Flash, and more.1317 npm114MIT
TDQS
Scored across 3 tools
Each tool targets a distinct media type: image, video, and document file. The purpose of each is clearly separated by the input format, leaving no ambiguity about which tool to use for a given source.
All tools follow the consistent pattern `vision_analyze_<type>`, making it easy to predict the tool name for new media types. The verb `analyze` and prefix `vision_` are used uniformly.
Three tools cover the core capabilities of the server (image, video, and document analysis) without unnecessary bloat. This is a well-scoped set for a vision-focused server.
The set covers the primary media types (image, video, document), but local video and file inputs require public URLs, which could be a usability gap. Missing audio analysis is a minor omission but not core to vision.