"Recently updated information from 2 hours ago" matching MCP servers:

Provides tools to monitor host system health including CPU load, disk usage, and network status while enabling file system management tasks like searching and moving files. It includes built-in safety guards to prevent operations on critical system directories.

A comprehensive Node.js server implementing Model Context Protocol (MCP) that enables filesystem operations, process management, and terminal session handling with an enterprise-grade security approach.

An MCP server that gives LLM clients access to a SQL Server database and the local filesystem, including file operations and image handling.

Enables conversion of Markdown content into PDF documents with customizable paper formats and orientations. Supports both inline Markdown text and file path inputs, automatically generating PDFs using Playwright and Chromium.

Enables AI-powered PDF manipulation through natural language commands, integrating with Claude to perform operations like merging, splitting, encrypting, optimizing, and analyzing PDFs.

Enables AI agents and users to upload and download files via MCP, generating shareable links and identifier codes. Files are automatically deleted after 24 hours.

Enables users to log into their university Moodle in a dedicated Chrome profile, choose courses from their real module list, and incrementally download lecture files to local versioned folders while preserving older versions of updated materials. Also exposes tools to check login and connection status, discover courses, list resources, and inspect per-item sync results.

Enables searching and retrieving local Granola meeting notes, including transcripts, AI-generated summaries, and action items. It supports filtering by date or attendee and automatically reloads when the local Granola cache is updated.

MCP server to drive a local JDownloader 2 instance through its entire download lifecycle, including adding links/containers, linkgrabber management, queue control, priority, force-start, progress tracking, and cleanup.

Gives an existing AI agent local stdio tools to list, read, create, and edit .kinoscript.json audio-visual scripts in a single folder on your machine. Writes are validated, atomic, confined to that folder, and optionally guarded by an updated-at check so concurrent edits aren't silently overwritten.

PDF extraction that actually works. The only extractor that audits every page. #2 on opendataloader-bench. 5 MCP tools for AI agents: metadata, convert, analyze, batch, structured extraction.

An MCP server for ROS 2 development that enables controlled creation of workspaces, packages, nodes, launch files, and tests within a sandboxed directory, with secure filesystem boundaries.

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.

Enables file-only MCP workflows for Delta DOP-B/DOPSoft 2 and DOP-100/DIAScreen HMI engineering through isolated backends and explicit source/target/plan contracts, supporting audited preview, validation, approval, application, new-only save, and diff operations while preserving unknown native bytes.

A Model Context Protocol server that provides DLIS (Digital Log Interchange Standard) file analysis capabilities. This server enables LLMs to extract information from DLIS files, including channel data and metadata, with support for hierarchical data structures.

Enables users to read Moodle course information, list courses, outlines, resources, assignments, and deadlines, and download or extract text from course files locally via an MCP-compatible client.

A Model Context Protocol server that enables Claude to fetch, process, and extract information from PDF documents, including LaTeX mathematical equations.

Reads A5:SQL Mk-2 ER diagrams and SQL files locally, making them accessible to AI tools via the MCP protocol without executing SQL or writing to databases.

Enables extracting text and metadata from local PDF files, inspecting page and file information, merging multiple PDFs, and splitting PDFs into single-page documents through MCP tools.

Enables AI assistants to append completed work items to the checklist of the newest daily log file in a configured directory, keeping notes updated without exposing file paths.