Enables intelligent document processing by extracting text, classifying document types, and generating structured summaries from PDFs and images using vision LLMs.
Enables AI agents to search for reference images using natural language queries, aggregate results from multiple image sources, and interactively select, refine, and download images through tool calls.
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.
Privacy-first MCP server for macOS that allows AI agents to search local images using natural language descriptions, leveraging MLX CLIP embeddings and LanceDB for fast, fully offline search.
Enables natural language search of local photo archives using AI-powered semantic understanding, with integration into Claude Desktop via the Model Context Protocol.
MCP server that turns articles, transcripts, and markdown into LinkedIn carousel PDFs, Instagram PNGs, and Threads PNGs. Content in, slides out. No web UI, no cloud service.
An MCP server that searches the web for images, creates a numbered contact sheet for visual selection, and downloads the chosen images with provenance metadata. Works without an API key.
A Model Context Protocol server that provides web and image search capabilities through Google's Custom Search API, allowing AI assistants like Claude to access current information from the internet.
An AI-powered MCP server that extracts structured data from Indian identity documents (Aadhaar, Passport, PAN, Driving License) using OCR, enabling Claude Desktop to read and process document images locally.
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 deterministic visual and structural analysis of PDF and DOCX documents, extracting measurable evidence such as blur, OCR confidence, and image anomalies for auditable forensic workflows.