"Uptime Kuma" matching MCP servers:

Multi-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.

An MCP server that adds visual understanding to text-only LLMs via image understanding, OCR, and image comparison tools, with multi-provider fallback and context-aware Focus Hint for precise descriptions.

Enables creating and polling Luma video modification tasks, fetching task status, and checking pricing via the RunAPI API.

Create videos and images using Luma AI, this MCP server handles all API functionality for Luma Dream Machine from Claude Desktop.

Enables image and video generation using Luma's API, supporting multiple models, aspect ratios, and advanced features like keyframes and style references.

Adds image understanding to AI coding clients that lack native vision, letting them analyze screenshots, error messages, UI mockups and documents through a unified image_understand tool. Supports multiple vision LLM providers with automatic cropping, compression and retry handling.

Provides tools to interact with RunwayML and Luma AI APIs for video and image generation, including text-to-video, image-to-video, prompt enhancement, and management of generations.

Adds image understanding to AI assistants that lack native vision, letting them analyze code screenshots, error captures, UI layouts, documents, and OCR content through a single unified image_understand tool. It routes requests across multiple vision model providers such as GLM-4.6V, DeepSeek-OCR, Qwen3-VL, Doubao-Seed, and Hunyuan, handling large-image cropping, compression, retries, and HTTP/Docker deployment.

Provides a unified image-understanding tool for AI coding assistants without native vision, letting them analyze screenshots, error messages, UI layouts, and documents through multiple vision LLM providers. Supports local files, remote URLs, and Data URIs with preprocessing, OCR, multi-crop, retries, and HTTP/Docker deployment.

A multi-model vision MCP server that gives image understanding to AI coding assistants lacking native vision, letting them analyze screenshots, error messages, UIs, and documents through a single image_understand tool. It routes requests to major vision LLM providers such as GLM, DeepSeek-OCR, Qwen-VL, Doubao, and Hunyuan, with automatic image preprocessing, cropping, and retries.

Enables AI coding assistants without native vision to analyze images — screenshots, error messages, UI layouts, and documents — through a single image_understand tool. It routes requests across multiple vision LLM providers (GLM, DeepSeek-OCR, Qwen, Doubao, Hunyuan, or any OpenAI-compatible endpoint), with automatic cropping, compression, and retry handling for text-dense or large images.

Gives AI coding models without native vision the ability to analyze images — screenshots, error messages, UI mockups, and documents — through a single unified image understanding tool. It routes requests to multiple vision model providers (GLM, DeepSeek-OCR, Qwen, Doubao, Hunyuan, or any OpenAI-compatible endpoint) with automatic cropping, compression, OCR-friendly handling, and retries.

Enables AI coding clients that lack native vision to analyze screenshots of code, errors, UIs, and documents by routing images through a single image_understand tool backed by multiple vision LLM providers such as GLM-4.6V, DeepSeek-OCR, Qwen3-VL-Flash, Doubao-Seed, and Hunyuan-Vision. Handles local files, remote URLs, and Data URIs with automatic multi-crop, compression, retry, and OCR-friendly preprocessing, and can be deployed over stdio or shared HTTP/Docker for multiple clients.

Enables AI clients and coding models that lack native vision to analyze images — screenshots, error captures, UI mockups, documents and OCR — through a single unified image-understanding tool. Routes requests to multiple vision model providers (GLM, DeepSeek-OCR, Qwen, Doubao, Hunyuan or any OpenAI-compatible endpoint) with automatic cropping, compression and retry handling.

Enables AI assistants without native vision to analyze screenshots, code errors, UI, documents, and OCR images by routing requests to multiple vision model providers. It supports a unified image-understanding tool with local files, remote URLs, and Data URIs.

Enables AI coding models without native vision to analyze images such as screenshots, error messages, UI layouts, and documents through a single image_understand tool. Supports multiple vision LLM providers including GLM-4.6V, DeepSeek-OCR, Qwen3-VL-Flash, Doubao-Seed-1.6, Hunyuan-Vision, and any OpenAI-compatible endpoint.

Enables AI clients and coding models without native vision to analyze images — screenshots, code errors, UI layouts, documents and OCR — through a single image_understand tool. Routes requests to multiple vision model providers with automatic preprocessing, multi-crop, compression, retry, and optional HTTP/Docker deployment for shared access.

Adds image understanding to AI coding clients that lack native vision, letting them analyze screenshots, error messages, UI layouts, and documents through a single unified tool. Routes requests across multiple vision LLM providers with automatic preprocessing, multi-crop handling for large or text-dense images, and retry logic.

A multi-model vision MCP server that gives image understanding to AI coding models lacking native vision, letting them analyze screenshots of code, errors, UI, and documents or perform OCR. It routes requests through major vision LLM providers and can be shared over local networks via HTTP or Docker.

Enables AI coding models without native vision to analyze screenshots, errors, UI, documents, and OCR images through a single image_understand tool using multiple major vision LLM providers.

A server that provides Luma AI's video generation API as the Model Context Protocol (MCP)

Enables AI coding assistants without native vision to analyze images such as screenshots, error messages, UI mockups, and documents through a single image_understand tool backed by multiple mainstream vision model providers. It handles local files, remote URLs, and Data URIs with automatic cropping, compression, and retries, and can be deployed locally via stdio or shared over HTTP/Docker.

Provides a unified image-understanding tool for AI assistants without native vision, letting them analyze screenshots, error messages, UI layouts, and documents via multiple vision LLM providers. It supports local files, remote URLs, Data URIs, OCR, multi-crop processing, and standard MCP clients.

Enables AI assistants and coding models without native vision to analyze images—screenshots, error messages, UIs, documents and OCR text—through a single unified image_understand tool. Supports multiple vision LLM providers (GLM-4.6V, DeepSeek-OCR, Qwen3-VL, Doubao, Hunyuan, or any OpenAI-compatible endpoint), with automatic image preprocessing, cropping and retries, over stdio or shared HTTP/Docker deployment.

Enables AI coding assistants without native vision to analyze screenshots, errors, UI designs, and documents through a unified image understanding tool backed by multiple vision model providers. Supports local files, remote URLs, Data URIs, OCR, multi-crop processing, and stdio or HTTP deployment for shared access.

Enables AI assistants and coding models without native vision to analyze screenshots, code errors, UI, documents, and OCR images through multiple vision LLM providers via a single image_understand tool.

Enables text-to-image generation using Zhipu AI's CogView-4 API. Supports generating images from text prompts with configurable size and quality parameters through MCP-compatible clients like Claude Desktop and Cline.

Adds image understanding to AI coding assistants that lack native vision, letting them analyze screenshots of code, errors, UIs, and documents through a single image_understand tool. Supports multiple mainstream vision LLM providers, with automatic preprocessing such as multi-cropping, compression, and retries.

Adds image understanding to AI coding clients that lack native vision, letting them analyze screenshots, error messages, UI layouts, code and documents through a single unified image_understand tool. Routes requests across multiple vision LLM providers (GLM, DeepSeek-OCR, Qwen, Doubao, Hunyuan, or any OpenAI-compatible endpoint) with automatic multi-crop, compression, retry and SSRF-safe preprocessing.

Enables AI assistants that lack native vision to analyze screenshots, error messages, UI layouts, and documents through a single image_understand tool. Routes each request to one of several vision LLM providers (GLM-4.6V, DeepSeek-OCR, Qwen3-VL, Doubao-Seed-1.6, Hunyuan-Vision, or any OpenAI-compatible endpoint) with automatic cropping, compression, and retry handling.