"namespace:.run.mcpize.bintu-web-reader" matching MCP servers:

Integrates Jina.ai's Reader API with LLMs for efficient and structured web content extraction, optimized for documentation and web content analysis.

MCP server for reading HWP and HWPX documents without Hancom Office. Extracts text, tables with merged cells, and hidden memos, compatible with various MCP clients.

MCP server for AI-assisted PDF reading with pagination, search, and page navigation.

MCP server that reads Google Docs and Google Sheets content for AI assistants like Claude.

Enables AI assistants to read and extract text content from PDF, Excel, and Word documents via the Model Context Protocol.

A Model Context Protocol (MCP) server that allows interaction with PDF and EPUB documents, designed to work with Windsurf IDE by Codeium.

MCP server for comprehensive PDF processing including text extraction with OCR, keyword search with regex, table extraction, and page preview as Base64 PNG images.

Enables AI tools to extract Feishu documents (Docx/Wiki) via Feishu Open API and convert them to Markdown format with local image downloading and authentication.

An MCP (Model Context Protocol) server specialized in deciphering PDF internal structures.

Enables intelligent navigation and extraction of documentation from websites, allowing Amazon Q to automatically discover relevant pages, extract clean content, and retrieve code examples from web documentation.

A PDF MCP server for extracting text, rendered pages, tables, links, annotations, outlines, metadata, and text statistics from PDF files.

A local-first MCP server for web search and documentation fetching, providing free DuckDuckGo search, URL-to-markdown conversion, and library docs from npm, PyPI, crates.io, Go, and GitHub with caching.

This server allows Large Language Models to consume S1000D data and publication modules as structured information instead of raw XML. It enables reading the content's hierarchy, applicability to specific products, and document verification status.

An MCP server that enables AI assistants to read, search, and analyze PDF files from local paths or URLs. It provides tools for extracting specific page ranges, searching for terms, and retrieving document metadata.

A Model Context Protocol server that enables AI assistants to read PDF files, extract text, retrieve metadata, read specific pages, and search within PDFs.

A Model Context Protocol server that enables the extraction of text, metadata, and embedded images from PDF files. It provides tools for searching text with context, reading specific pages, and counting total pages within a document.

Enables AI agents to securely read and extract information from PDF files including text content, metadata, and page counts from both local files and URLs within the project context.

A version-aware cache for web research that stores and serves documentation references, preventing models from re-researching the same topics across sessions.

A Model Context Protocol server that extracts and processes content from PDF documents, providing text extraction, metadata retrieval, page-level processing, and PDF validation capabilities.

Enables reading and parsing Swagger/OpenAPI specifications to list API endpoints, get detailed endpoint info, search APIs, and generate TypeScript types for request/response.