"Modal" matching MCP servers:

Facilitates running Python code in a sandbox and generating images using the FLUX model via an MCP server compatible with clients like Goose and the Claude Desktop App.

Enables AI agents and MCP-compliant clients to extract visual data from charts and graphs into structured markdown tables using deterministic, zero-dependency Python.

Enables MCP-compatible clients to call TokenHub's image generation and editing APIs through natural language, supporting text-to-image, image-to-image, and configurable model and endpoint settings.

Integrates xAI's Grok APIs into Claude Code to enable image and video generation, real-time web searches, and multi-modal image analysis. It provides a suite of tools for interacting with Grok models directly through natural language prompts during a Claude session.

Enables AI agents to analyze videos and images using Qwen3-VL deployed on Modal, supporting hours-long videos with timestamp grounding, text extraction, video summarization, and Q\&A with 256K context window.

Enables AI assistants to generate images and videos through natural language using ImaginePro's API. Supports text-to-image generation, video creation, image upscaling, variants, inpainting, and multi-modal generation with real-time progress tracking.

Enables Claude Code and Codex to directly invoke Xiaomi MiMo's full-modal capabilities including multimodal dialogue, image/video understanding, TTS, voice cloning, and ASR through MCP tools.

Enables AI-powered 3D model generation from text and images with PBR textures, supporting blockchain authentication and MCP integration.

Enables real-time fusion of 2D/3D visual bounding boxes, head-pose gaze vectors, and acoustic beamforming azimuth angles into cross-modal focal salience scores to resolve deictic spatial references for multimodal agents.

Enables AI agents to fuse 2D/3D visual bounding boxes, user head-pose gaze vectors, and acoustic beamforming azimuth angles into cross-modal focal salience scores. It also resolves deictic spatial references in real time, running as a zero-dependency Python MCP server over JSON-RPC stdio.

An MCP server providing multi-modal generation tools based on Volcengine's Jimeng AI, supporting high-quality 4K image creation, intelligent image editing, and video generation. It enables users to perform complex visual tasks directly within clients like Cursor and Claude Desktop.

MCP server for FG-CLIP embedding services enabling multi-modal similarity computation for text and images.

An MCP server that lets AI agents drive a running Adobe Photoshop from natural language — documents, layers, text, masks, selections, filters, adjustments, Smart Objects, artboards, generative tools and export — through a 9-tool facade backed by 134 operations. A dual ExtendScript/UXP transport keeps reads, saves and exports working even when Photoshop is modal, returning honest busy/timeout errors instead of silent hangs.

Enables semantic search, image search, and cross-modal search functionalities through integration with Jina AI's neural search capabilities.

Local MCP server that provides multi-modal vision capabilities to single-modal base models via API, supporting multi-turn iterative image recognition and document image parsing.

Renders text into PNG canvases for use as input to local vision models. It exposes a generate_vision_text_image tool that returns standards-compliant MCP ImageContent, allowing capable clients like LibreChat to display the generated images directly.