"A search for information related to PDF files" matching MCP servers:

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

Enables PDF document processing including text, image, and table extraction, as well as intelligent classification and similarity analysis across multiple languages.

Provides tools for extracting text, performing OCR on scanned documents, and retrieving images from PDF files. It enables Model Context Protocol clients to process PDF content page-by-page through specialized extraction tools.

A PDF processing server that extracts text via normal parsing or OCR, and retrieves images from PDF files through the MCP protocol with a built-in web debugger.

Enables precise extraction of PDF content, including text coordinates, vector shapes, images, and on-demand raster rendering, for use cases like reconstructing design files.

Extracts images from PDF files, allowing LLMs to access and analyze embedded images from local PDF documents.

Enables AI assistants to inspect and fill fillable PDF forms by exact field name, then render and OCR the resulting page to confirm every value is actually visible, returning verdicts of VISIBLE, INVISIBLE, RENDER-ONLY, or MISSING.

Enables AI agents to perform local-first PDF processing entirely on-device, including OCR write-back to make scans searchable, unlocking and re-encrypting PDFs, splitting/merging/rotating pages, and compressing files, with no cloud calls or file uploads.

Enables AI coding agents to inspect digital or scanned PDF forms and worksheets, map detected answer slots through a virtual Excel/Set-of-Marks view, and inject baseline-snapped text, multi-line answers, or option marks into clean output PDFs. Supports visual verification of completed pages.

Enables PDF reading through MCP with text extraction, Chinese OCR for scanned documents, page rendering, and keyword file search from any compatible MCP client.

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

Enables AI agents to extract text locally from PDF files through a STDIO tool, returning full-document text, page-level paragraphs, extraction methods, warnings, and basic table readability, with English/German OCR fallback for scanned pages.

Inspects local PDF files, extracting text, counting pages, and performing OCR on scanned PDFs using standard libraries.

A local stdio MCP server that reads a PDF page from a local path or authorized download URL and renders it in memory, returning a real PNG image block plus page metadata. This lets an agent's vision model actually see handwriting, formulas, arrows, colors, and figures instead of only extracted text, with configurable DPI and clipping while reporting page count and size.

Enables AI-powered PDF editing and generation via natural language prompts using Google Gemini, with local storage and OCR for searchable text.

Enables AI assistants to convert CSS-animated SVGs into videos (MP4/WebM/MKV/MOV) and animated images (aPNG/GIF) with frame-accurate rendering and transparency support.

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.

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

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.

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.

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.

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 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.

Enables MCP clients to turn direct video URLs and chosen start/end times into ready-to-post vertical 9:16 MP4 clips with animated burned-in captions, thumbnails, and SRT files, including batch processing for multiple highlights.

Turns a single image of an object into a textured 3D model (GLB with web-ready copy and six-view previews) on your own NVIDIA GPU, returning the written files and a preview. Runs locally as an MCP tool or, optionally, offloads the job to hosted GPUs with an API key.

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.

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.

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.