"Understanding and Building Probability Density Functions (PDF) Models" matching MCP servers:

MCP server for multimodal understanding and object grounding (bounding boxes) across images, videos, and documents, with support for multiple AI providers (Zhipu GLM-V, OpenAI GPT-4o, Anthropic Claude, or any OpenAI-compatible endpoint).

Saves the user's exact words as immutable, SHA-256-hashed captures before anything else, then derives events, entities, context cards, and causal hypotheses — every fact traceable to its verbatim source. Local-first personal memory for Claude Code, Codex, and any MCP client.

Provides 12 tools to query South Korean building register data, including title sheets, floor details, and official house prices via the data.go.kr API. It enables users to perform smart building lookups and region code searches using natural language.

An MCP server that analyzes local or remote GitHub repositories, providing intelligent code context and structure to AI coding assistants.

Provides comprehensive building and office address information queries for enterprises in China, including fuzzy enterprise search, office address details and statistics, and building information queries to support geographical distribution and occupancy analysis.

Integrates Xiaomi MiMo's multimodal API to enable understanding of images, audio, and video through natural language prompts.

A local-first MCP server that ingests PDFs, extracts structure, and provides semantic search and sequential navigation tools for AI clients to query and learn from documents.

Enables PDF processing and analysis including text extraction, metadata retrieval, search, page manipulation, splitting/merging, conversion to images, and form handling.

An MCP server for reading, rendering, and searching PDF files, specifically optimized for LLMs to extract text, tables, and technical diagrams. It enables metadata retrieval, multi-format text extraction, and page-to-image rendering using PyMuPDF.

A Model Context Protocol server that enables AI agents to read, search, and extract content from PDF files.

Full-stack PDF intelligence MCP server for extracting, manipulating, annotating, converting, validating, and RAG-searching PDFs through a unified tool surface and React workbench.

MCP server for Aspose PDF Cloud, enabling PDF storage, conversion, and extraction operations (merge, split, text/table/image extraction) via CLI and MCP.

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

A quickstart template to build and deploy a remote MCP server on Azure Functions using Python, secured with keys and HTTPS.

An MCP server that exposes Marker for high-quality PDF OCR and conversion, providing a tool to convert PDFs to markdown, JSON, or HTML with optional LLM-enhanced mode.

Extracts text and tables from PDFs for AI agents via MCP, enabling structured data retrieval from invoices, reports, and statements.

Enables AI-powered extraction and analysis of PDF documents with 40+ specialized tools for text, tables, images, layout analysis, security assessment, and document intelligence. Supports both text-based and scanned PDFs with OCR capabilities.

This server converts PDFs to markdown with intelligent academic paper detection and dual processing engines (marker-pdf for academic content, PyMuPDF for general documents), supporting URL and local file handling, page extraction, batch processing, and PDF link crawling for Claude Code analysis.

MCP server for full-text search across PDF document collections with offline indexing, ranked results, snippets, and page rendering.

Relays a result screenshot to Slack so you can review a coding agent's output without opening the app.