"How to read document contents" matching MCP servers:

MCP server for EveryPage that lets an AI assistant turn a PDF into a tracked share link and report who read it, how far they got, and where they stopped.

Verifiable document intelligence for AI agents. Extract text, tables, and structured data from PDFs and URLs. Summarize, answer questions, check claims, and translate — all with cited evidence. Store tamper-evident evidence bundles with cryptographic signatures and on-chain attestation via Base L2. Cross-document semantic search and Q&A across named collections. Pay per call with USDC

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

Enables AI models to interact with IBM FileNet Content Manager for document management, folder operations, metadata handling, search, and content extraction through a standardized interface.

Provides AI tools with access to ProudNet documentation through search, page retrieval, and section listing capabilities. Enables users to query ProudNet networking library documentation using natural language.

Enables interaction with the SendForSign API to list document templates and read template content for electronic signature workflows.

What is PandaDoc MCP? PandaDoc MCP (Model Context Protocol) server connects AI agents directly to PandaDoc's document workflow — creating, sending, and tracking contracts and agreements without leaving your AI client. How to use PandaDoc MCP? To use PandaDoc MCP, connect your PandaDoc account, provide the required API credentials, and configure the appropriate MCP client.

This MCP server lets AI agents connect to Figma to read, analyze, create, and modify designs, including elements, styles, assets, and code generation. It works with free Figma accounts and supports parallel multi-agent use across MCP-compatible clients.

Bridges AI agents with watsonx.data document libraries, enabling natural language queries and intelligent retrieval from document libraries.

Provides read-only access to the CatalogAPI global rewards and gift card API, enabling assistants to answer questions about reward coverage, catalog contents, and integration via live data.

Provides a universal read path for agents to extract facts, metadata, and provenance from local files and guarded remote URLs without using generative LLMs.

Enables AI agents to search, deep-read, and build knowledge bases from Markdown, PDF, DOCX, and PPTX documents via MCP tools for retrieval, document navigation, and ingestion.

Renders PDFs from HTML templates or saved templates and spreadsheet data, with batch job support and document retrieval.

Enables AI agents to send emails and manage tasks in Microsoft To Do with scoped, low-risk access to Microsoft Graph.

Search, document and execute authenticated API calls across all your apps (Gmail, Slack, Stripe, Notion, GitHub, and more) through 4 universal tools whose context footprint stays constant no matter how many connections you add. Hosted remote server with OAuth at https://mcp.withone.ai/mcp, or run locally via npx @withone/mcp.

Provides Web3 founders with tools for project scoring, portfolio matching, fund matching, hackathon discovery, jurisdiction analysis, Twitter audit, and smart contract security review. Works with MCP-compatible assistants without transmitting file contents.

Screen-reader navigation cost analyzer. Measures how hard it is for assistive-technology users to discover, reach, and operate interactive targets on the web.

Semantic memory for AI builders: capture the tacit engineering know-how that never reaches your docs, recall it the moment it applies. Built in Rust on Postgres and pgvector.

Enables AI assistants to generate DOCX and PDF documents from DocMake templates through natural language, including template listing, field inspection, document rendering, DOCX import, and usage tracking.

Read-only access to a self-hosted GeoLens geospatial catalog: dataset search, schemas, GeoJSON features, saved maps, and sandboxed read-only SQL over PostGIS.