"How to read document contents" matching MCP servers:

Provides access to microCMS documentation, enabling AI assistants to search and retrieve the latest document content.

Enables parsing and extraction of content from various document formats (PDF, Word, Excel, PowerPoint) into Markdown format using the Niutrans document API.

Provides tools and resources for managing in-memory documents, allowing users to read, edit, and list document contents via the Model Context Protocol. It includes features for formatting documents to Markdown and accessing document-specific resources.

Converts Markdown files to Atlassian Document Format and publishes them to Confluence, with support for rendering Mermaid diagrams as PNG attachments.

Local document intelligence for AI agents — extract text, detect tables, read metadata, analyze structure, search keywords, and detect language from PDF and DOCX files. No cloud API required, no API key needed.

Enables comprehensive content management through Markdown processing, HTML rendering, intelligent fuzzy search, and document analysis. Supports frontmatter parsing, tag-based filtering, table of contents generation, and directory statistics for efficient content organization and discovery.

Enables conversion between PDF/Office documents and structured JSON, supporting extraction and generation of document content.

A comprehensive document analysis server that performs sentiment analysis, keyword extraction, readability scoring, and text statistics while providing document management capabilities including storage, search, and organization.

Exposes an internal engineering knowledge base to AI assistants, allowing users to search and retrieve standards, runbooks, and architecture decisions. It supports RAG-enhanced search, document scraping, and specialized prompts for incident investigation and code reviews.

Enables interaction with Siemens Polarion requirements management system through natural language. Supports authentication, project management, work item queries, document access, and requirements analysis.

A Code Mode MCP server that provides AI coding agents with curated, per-stack documentation as typed tools, enabling efficient document access and search across multiple stacks.

Provides a documentation search MCP tool (search_docs) that enables AI agents to retrieve relevant chunks from BDC documentation using semantic embeddings and keyword search, with filtering by document type and date.

Enables local conversion of PDFs to Markdown, with automatic OCR fallback for scanned pages, image extraction, and page-by-page structure preservation.

Official MCP for Carbone - Document Generation, Document Conversion, and Universal Templating.

A Model Context Protocol server that enables AI assistants like Claude to interact with Outline document services, supporting document searching, reading, creation, editing, and comment management.

A Model Context Protocol server for querying and reading articles from a how-to documentation portal, with search and retrieval tools scoped to the token's user permissions.

Teaches AI coding agents how to reason correctly about MetaMask Embedded Wallets / Web3Auth architecture, SDK choice, key derivation, auth flows, and common integration pitfalls.

Enables searching the YÖK National Thesis Center and retrieving thesis contents in Markdown format for LLM applications. It allows users to perform detailed searches based on criteria like author, university, and subject while providing programmatic access to thesis metadata and PDF content.

Enables local document search and reading across formats like docx, pdf, md, and more, providing tools for listing, searching, and reading documents.

This server enables users to interact with proprietary Digitale Bibliothek 5 data formats, specifically the .DKI structure. It allows retrieval of volume metadata, hierarchical table of contents, and decoded text content from the stored CD volumes.

Provides read-only tools to search, read, and look up Natural API documentation from an AI agent, enabling documentation lookup without credentials.

Lets AI assistants search and read vendor documentation from the TIA Portal and Industrial Operations X portals in real time, exposing search, table-of-contents, publication-listing, and Markdown page-reading tools.

Enables document format conversion between various formats (Markdown, HTML, PDF, DOCX, LaTeX, EPUB, and more) using Pandoc, preserving formatting and structure while supporting both direct content transformation and file-based conversions.

Enables AI assistants to answer British Columbia employment law questions — overtime, breaks, statutory holidays, pay, leaves and termination — from the current official text on BC Laws, in English or Chinese, with the act, section number, link and official "current to" date. Exposes tools to locate acts, browse a table of contents, retrieve and search sections, and map everyday or Chinese terms to the wording the statute actually uses.

Provides fresh project context to coding agents by combining Markdown documentation and live Git state, enabling deterministic startup briefs and bounded document retrieval for MCP-compatible tools.

Enables LLMs to chat with long PDFs using a reasoning-based, tree-structured document index that navigates content like a human would, without requiring vector databases or hitting context limits.

MCP server that enables searching and reading binary document files (PDF, DOCX, PPTX, XLSX, ODT, ODS, ODP, RTF, EPUB) using regex patterns and retrieving content by sections.

A Model Context Protocol server that integrates with Nutrient Document Web Service, allowing AI assistants to perform advanced PDF operations including digital signing, document generation, editing, OCR, watermarking, and redaction.

An MCP server that provides utility tools for markdown processing, including ADF-to-markdown conversion, table formatting, and table of contents management.

Look up how engineers actually pronounce project / product / jargon names (kubectl, nginx, JSON, Pydantic, JWT) — 1452+ entries with IPA, respelling, source citation, and confidence level.