"让AI大模型读取和分析本地文件（Word/Excel/PDF/Markdown/代码等）的方法" matching MCP servers:

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

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

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

Splits Markdown documents into hierarchical sections with parent-child and sibling relationships, enabling structured document access for AI assistants.

Provides Markdown utilities: converts Markdown to plain text, extracts links and headings. Part of the Pipeworx MCP gateway.

Enables reading and optionally editing existing Markdown files under a configured root folder, including section-level queries, overwrites, appends, deletions, and front matter management, over stdio with no network dependencies.

Translates project README files into multiple languages via MCP server or standalone pipeline, using local LM Studio models for translation, critique, and revision.

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.

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 bidirectional Markdown-to-Confluence sync, enabling download and publish of Confluence pages as Markdown with images, frontmatter tracking, and dry-run safety.

Converts Markdown files and standalone Mermaid diagrams into high-quality PDF or PNG documents using Puppeteer and SVG rendering. It supports custom CSS styling and provides tools for professional document generation from markdown-based content.

An MCP server for local PDF inspection that classifies, searches, extracts text and tables without uploading documents or relying on OCR, surfacing reliability warnings for garbled or scanned content.

Enables AI assistants to read local documents by converting PDFs, Office files, images, and audio to Markdown on-device, without uploading them.

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.

MCP server for PDF manipulation — create PDFs from Markdown with tables and formatting, fill forms, merge, split, encrypt, add QR codes, and more. 16 tools, zero external binaries, TypeScript-native. Install with npx -y @aryanbv/pdf-toolkit-mcp.

Memory-efficient MCP server for reading and splitting large PDF files page by page using PyMuPDF.

MCP server for markdown files — search, extract sections, list headings, find code blocks across docs.

Enables assistants to search a Zotero library, retrieve metadata and PDF text, and view PDF pages as rendered images so figures and layouts are visible.

This MCP server enables AI agents to view PDFs as accessible HTML with bounding-box citations, and provides tools for layout-aware parsing, schema extraction, cross-document Q&A, and PDF rendering.