"Using Python to Locate and Retrieve Browser Element Selectors" matching MCP servers:

Extracts text from images and browser screenshots locally using Tesseract.js, without sending image data to the LLM.

Routes one brief to the right image model across 60+ (gpt-image-1.5, Ideogram 3, Recraft V4, Flux), validates the output, and fans out to iOS/Android/PWA/favicon/visionOS/Flutter bundles. Works without an API key via Pollinations, HF Inference, Stable Horde, or host-LLM inline SVG.

Controls Google Flow for image and video generation from an AI agent. Enables generating images with models like Imagen 4, creating videos, managing characters and scenes via browser automation.

A streamlined MCP server for XMP metadata embedding with beautiful formatting and smart filename indicators, enabling metadata embedding, reading, validation, and report generation for lifestyle, product, and orbit schemas.

A full-featured secure MCP server for local file system operations, with built-in image processing, OCR and media tools. Fully compliant with the official Model Context Protocol specification, offering standardized request/response schemas, large-file streaming I/O, multi-transport remote deployment, and comprehensive text search & replace functionality for LLM agent integration.

Enables LLM agents to process local videos into timestamped, citable text documents and then query them through tools for listing videos, retrieving transcripts, and fetching specific segments, all fully offline.

Converts ComfyUI workflows into MCP tools for AI agents to generate images, videos, and other multimedia content.

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

MCP server for ingesting UI screenshots, Figma MCP node JSON, or hybrid Figma-plus-screenshot sources into a cross-platform design-to-code artifact pipeline.

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.

Provides governed MCP tools for a controlled, AI-assisted asset-change pipeline, featuring natural-language requests, mandatory approvals, execution-time revalidation, and complete audit.

Converts local images or remote image URLs to Base64 format via the MCP protocol, enabling AI assistants to process images.

MCP server for MarkItUp's AI image-annotation pipeline. Generate polished marketing-visual variations of any screenshot, regenerate, AI outpaint, and remove backgrounds — powered by Claude analysis + Gemini rendering.

Enables AI agents to drive Google Flow through a real Chrome profile to generate images, videos, characters, and scenes without sharing credentials.

Enables agents to discover available still-image animation models, obtain credit quotes without charge, submit one explicitly approved generation job, and poll the resulting short clip.

Enables Claude Code to convert PDF files to high-quality PNG images, download academic papers, and batch process PDFs with automatic folder organization.

Enables MCP clients to operate Google Flow through a visible browser, supporting login, project tracking, reference upload, generation submission, and media download with local validation.

Enables AI clients to generate animated videos from natural language prompts, handling scriptwriting, voiceover synthesis, and MP4 rendering.

An MCP server that gives LLM clients access to a SQL Server database and the local filesystem, including file operations and image handling.

MCP server that enables AI agents to control Google Flow for image and video generation using your own Google account.