"Setting Up MCP (Minecraft Control Panel or Related Tool) Helper" matching MCP servers:

Enables Claude to create and edit Minecraft skins in real time inside the Minecraft Skins Editor, with painting tools, undo/redo, and skin downloads.

An MCP server that adds vision capability to any LLM by forwarding images to OpenRouter vision models, returning text analysis. Supports image analysis, model listing, and config diagnostics.

Enables AI agents to access real-time touchless gesture recognition, 3D hand landmarks, virtual key event injection, facial telemetry, sensitivity adjustment, and system health diagnostics through the Model Context Protocol.

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.

Generates quality control plans and inspection reports from technical-drawing PDFs: tolerances, fits, threads, GD&T and surface finishes are extracted automatically by Imnoo's drawing analysis, numbered as balloons with acceptance limits and measuring instruments, and exported as a ballooned drawing PDF, an inspection package and an Excel measurement report.

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.

Enables AI agents to process files locally — OCR images, extract text from PDFs and DOCX, and describe images using local vision models, all without sending data to external services.

Enables detection of AI-generated content in images, videos, audio, and text via the AI or Not API. Supports media analysis tools for deepfakes, synthetic voices, and AI-written text.

Provides comprehensive computer control capabilities including mouse and keyboard automation, screen capture, OCR text recognition, and window management through MCP protocol.

Enables AI agents to create, edit, validate, and package pixel-art textures for Minecraft resource packs through deterministic MCP tools.

Enables AI assistants to access and control network cameras to capture images and perform analysis including brightness detection, color distribution, and edge detection.

Enables AI-powered generation of styled QR codes with 10 design presets, supporting single or batch creation with custom logos and formats (SVG/PNG) directly from AI 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 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 AI assistants to create Material Maker node graphs from natural language, validate them against the node catalog, and render them headlessly to PBR texture maps and editable .ptex files.

Enables AI agents to drive a local asset review loop: list and fetch paired original/output items (including image content for visual comparison), mark pass/reject/unsure with problem tags and region annotations, batch-review scoped selections, and export results as JSON or CSV. Also supports round archiving, detecting stale results after source re-renders, and listing previous-round rejects.

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

Enables intelligent identification and validation of compound data from documents and images, then automatically draws compound structures using local ChemDraw software with academic formatting.

A local MCP server for generative image description, providing prose captions, OCR, and LoRA dataset caption sidecars via Florence-2, with deterministic decoding and an honesty contract.