"A server for finding PDF documents" matching MCP servers:

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 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.

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.

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.

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.

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.

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.

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.

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.

An MCP server providing comprehensive PDF processing capabilities with 18 tools for text extraction, OCR, image conversion, metadata management, and optimization.

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.