"A tool for finding viral posts on platform X" matching MCP servers:

Enables analyzing a Douyin, Xiaohongshu, or Bilibili video link to generate a reusable editing blueprint with shot, caption, speech, rhythm, and visual analysis.

Enables AI agents to interact with X (Twitter) through 10 grouped tools and 69 actions, covering reading and searching posts, publishing threads, uploading media, managing Lists, sending DMs, and viewing images and video frames. Includes read-only and dry-run modes plus credential and rate-limit checks.

Enables AI assistants to drive a layered raster image editor with painting, shapes, text, filters, and internet-sourced images and fonts via MCP tool calls, with token-efficient rendering and export.

Enables AI agents to remotely operate visual design tools via MCP protocol, with composable architecture for image processing, file operations, and workflow automation.

Enables assistants to publish readable replies and status updates to e-ink displays and Home Assistant, with switchable characters and state retrieval through MCP tools.

Enables an AI assistant to batch-drive ArmorPaint headlessly via its native CLI and scripting engine, re-exporting projects at different presets and building procedural materials without opening the GUI.

Lets an LLM see what's on your screen by capturing an entire monitor or a specific application window.

Gives LLM agents spatial awareness inside Autodesk Maya, enabling scene inspection and measurement, aesthetic and engineering audits, camera planning, checkpoint/rollback safety, asset import, and viewport or render previews. Agents can also execute arbitrary Python in Maya to build and verify 3D scenes against engineering rules instead of writing blind.

Official MCP server for Theta EdgeCloud's On-Demand Model APIs, providing access to 20+ AI models including image generation, audio transcription, and LLMs, directly from MCP-compatible clients.

Enables AI-driven 3D modeling and scene creation in Blender, allowing LLMs to create, modify, and manipulate objects, materials, and assets through natural language.

Enables local OCR transcription of images using tesseract.js, with optional low-token AI-generated descriptions, folder batch processing, and compatibility with MCP clients like ChatGPT, Claude, opencode, and Cursor.

Empower LLMs with fine-grained visual understanding — detect, localize, and describe anything in images with natural language prompts.

Enables MCP clients to discover OpenRouter image and video models, generate and edit images, create variations, launch and monitor video jobs, and save resulting media into authorized local project directories with cost controls.

Provides vision capabilities to Reasonix, enabling analysis of images/videos, OCR, and comparisons via OpenAI-compatible vision models.

Bridges DeepSeek (text-only) with vision models via MCP, enabling image description and compression using any OpenAI-compatible visual API.

A customizable Model Context Protocol server implementation that enables AI models to interact with external tools including weather queries, Google search, and camera control functionality.

Enables AI assistants to programmatically inspect projects, create compositions and layers, apply effects, animate properties, and manage render jobs in Adobe After Effects through natural language.

Enables WorkBuddy and other MCP-compatible clients to generate images and videos from natural-language prompts through Agnes AI, returning online URLs and locally saved files.

A server that allows AI tools like Claude and Cursor to automate and control Photoshop through natural language commands, enabling tasks like editing PSDs, toggling layers, and generating marketing creatives.

A multi-agent human-computer interaction system that enables natural interaction through integrated visual recognition, speech recognition, and speech synthesis capabilities.

MCP server that exposes ComfyUI image and 3D generation as a single tool with smart prompt classification. It enables AI assistants to generate assets directly by selecting and running the appropriate ComfyUI workflow.

Enables image and video processing through FFmpeg, including compression, format conversion, resizing, and batch processing operations for common media formats.

Enables LLMs to drive Blender through socket-based two-way communication, letting them create and modify 3D objects, apply materials, run Blender Python, and fetch or generate assets while visually verifying results. Supports prompt-assisted 3D modeling, scene creation, and manipulation.

An MCP server for generating images and checking generation status through ComfyUI's API. It allows interaction with local ComfyUI instances by providing workflow-based image generation and status checking tools.

Enables AI agents to perceive and quantitatively verify physical hardware through USB webcams and RTSP/HTTP network streams, returning inline image content plus numerical metrics such as brightness, contrast, edge density, motion, SSIM baseline comparisons, and OCR text. Agents can watch feeds for visual conditions, correlate buffered frames with serial/log/MQTT events, and apply privacy masks and access controls.

Enables AI agents to inspect and drive Blender scenes directly, either through a live editor bridge on port 8190 or automatically via headless background CLI when Blender is closed. Provides token-efficient tools for scene outlining, object creation and modification, modifiers, materials, rendering, asset export, and arbitrary bpy script execution.

Enables AI assistants to control a Blender instance through MCP tools, supporting scene creation, editing, and asset exchange via HTTP and background CLI processes.

Provides tools to fetch IIIF manifests and retrieve specific image regions or scaled images for analysis. This server enables detailed interaction with International Image Interoperability Framework resources, supporting tasks like image description and transcription.

Enables interaction with Figma designs through the Figma API, allowing users to export images in multiple formats, extract style data and CSS, analyze design elements, and retrieve SVG code from Figma files. Supports batch operations and comprehensive design element analysis including images, vectors, and components.

Enables LLM clients to access crop yield predictions from RGB imagery, topic-based PDF literature, and soil lab/moisture CSV data.