Enables AI agents to read, edit, and create Microsoft Word documents (.docx) with support for rich text, tables, and images, deployable locally or via SSE.
An MCP server for document analysis that provides 21 tools for reading, text analysis, summarization, and data statistics, enabling AI clients to process and understand documents efficiently.
Provides MCP tools to count, list, and read local documents in formats like PDF, DOCX, Excel, HTML, and TXT, enabling natural language-driven document statistics and content inspection via qwen_agent.
MCP server for reading and writing .docx files. Exposes four paginated tools so agents can batch-read document content and styles, write content, and union style definitions.
Enables natural language interaction with local .docx files, allowing users to find, read, search, and summarize Word documents using friendly names and location hints.
Go MCP server for multi-format document access — PDF, TXT, MD, DOCX, CSV, images. 12 tools including OCR, search, table extraction, and URL fetch. Single binary, no runtime.
A local MCP server for reading and editing Word (.docx) documents with 33 tools for content, formatting, comments, page layout, and track changes, running locally via stdio.
A TypeScript MCP server that allows querying documents using LLMs with context from locally stored repositories and text files through a RAG (Retrieval-Augmented Generation) system.
A Word document processing MCP server that exposes a single tool (docx_process) routing to 63 operations covering creation, editing, formatting, and querying, with on-demand skill loading for context efficiency.
Enables comprehensive management of Microsoft Word documents with 30+ tools for reading, writing, formatting, template merging, image extraction, equation extraction, and style application.
A Model Context Protocol server that enables listing and reading PDF documents from a configured directory, extracting text content for MCP clients like Claude Desktop.
Provides comprehensive document processing, including reading, converting, and manipulating various document formats with advanced text and HTML processing capabilities.
Enables reading and analyzing Word documents with advanced features including table extraction, OCR image analysis, full-text search, and intelligent caching for optimized performance on large documents.
Makes local markdown documentation files automatically available to AI assistants through MCP, enabling them to search and read organized documentation folders without manual file registration.