"Information on Vulnerabilities in Systems or Networks" matching MCP servers:

Enables ChatGPT to access approved local Windows folders, run commands, control the desktop, and manage session history through a permission-bounded MCP server.

Enables ChatGPT's web interface to operate a real Mac by executing shell commands and reading or writing files over a reverse SSH tunnel, without installing a client or consuming API quota.

A read-only remote MCP server that searches and reads files from a personal Microsoft OneDrive folder via Cloudflare Workers, enabling live access without a local workstation or tunnel.

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.

Gives ChatGPT hands-on control of a local machine: reading, patching and executing code in approved project folders, running real interactive processes, managing plans and worker sub-chats, and driving the browser or desktop through user-granted permissions. Every capability is a switch inside an approved-folder sandbox, so nothing runs that the user did not explicitly enable.

Enables ChatGPT to work on a local project by reading and editing files, running shell commands, keeping terminals and desktop sessions open, and splitting work across durable workers whose context persists between tasks. Long-running work can be steered mid-flight, tracked with Goal, and carried into fresh chats via Compact & Resume.

Lets ChatGPT work directly on a local project by reading and editing files, running shell commands and tests, keeping terminals open, and using the user's desktop, all paired with an approved workspace folder. It also splits independent jobs across persistent workers that retain context, while riding the user's existing ChatGPT plan rather than Codex quota.

Enables AI assistants to inspect Ignition gateway backups, project exports and tag exports locally and turn them into an editable engineering reference and manual pack workspace. Runs over stdio so agents can explain, validate and complete the evidence-traced documents without uploading anything.

A local MCP server that gives Claude in the browser tools to interact with a Fedora machine, including file operations, system diagnostics, build tasks, and root actions via Polkit.

Enables file extraction, organization, and GitHub repository management through MCP tools, allowing AI agents to copy/move files, delete repositories, and automate workflows.

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 inspect, create, and report on IFC/BIM files locally, and to open models in a viewer with BCF viewpoint support.

Model Context Protocol server for the Apideck Unified API. Connect any MCP-compatible agent framework to 100+ accounting systems, HRIS platforms, file storage providers, and more through one integration. More information https://www.apideck.com/mcp-server

Converts Office documents, images, and e-books to PDF and transforms PDFs by merging, splitting, rotating, numbering, watermarking, compressing, protecting, or unlocking them, plus PDF-to-Word and PDF-to-image conversion, all driven by natural language. Files stay on the user's computer apart from the conversion itself, which runs on EU-hosted servers in France.

Enables an AI agent to host a shared folder or join an invite link as a participant in a collaborative editing session, reading, editing, and writing the files the room shares. Runs the same sync engine and wire protocol as editor clients, so an agent and a person or another agent converge on the same documents and see each other's changes.

Enables agents to run read-only coverage and staleness checks on local folders and documents, reporting missing periods or mismatched figures without writes, deletes, or network calls.

Enables AI agents to read, write, append, and delete content in Markdown files using structural selectors, without regex or string hacking.

MCP server that lets agents edit real Microsoft Word (.docx) documents - tracked changes, tables, styles, comments, content controls, and document properties - with every edit validated and previewed before saving. Built on the Open XML SDK (no Word automation); reads and writes documents in place through filesystem or SharePoint storage.

Enables saving, searching, retrieving, linking and importing AI work as plain markdown files with automatic provenance in a local folder the user owns. Runs entirely on the user's machine with no account, key or network calls, and never deletes anything.

Enables users to access local files, manage persistent notes via CRUD, fetch URLs, inspect system information, and analyze or transform text through MCP tools.