"Information about a Facebook page" 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.

Provides secure filesystem access for AI models through the Model Context Protocol with strict path validation, file operations, directory management, and system command execution within predefined directories.

Enables agents to compress JPEG, PNG, and WebP images to a target byte size, split PDFs by page or ranges, and remove image metadata while processing local files without sending file bytes over the network.

An HTTP MCP server that indexes large documents into exact-line-numbered sections, enabling AI models to locate, read, summarize, and edit parts of a document without ingesting the whole file.

A self-hosted MCP server that enables AI coding agents to read, edit, search, and run code in local projects with human review loops and policy controls.

Enables interaction with the WhkerDB shared PDF editor to manage collaborative rooms, file structures, and real-time annotations. It allows users to upload PDFs and images, manage note trees, and sync data across platforms through natural language.

Provides a secure workspace for AI-driven file management and Python script execution designed to run on Vercel. It enables tools for full file operations and code execution within a sandboxed environment.

MCP server for full-text search across PDF document collections with offline indexing, ranked results, snippets, and page rendering.

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

MCP server for Claude Code that consolidates routine setup actions like project scaffolding, skills, landing page builds, guard hooks, images, and icons into a single entry point.

Searches and browses local Claude Code and Cowork session histories stored on your machine, enabling questions about past work without uploading data.

Enables AI apps to edit PDFs on the local machine through natural language, merging, splitting, extracting, rotating, deleting, reordering and duplicating pages, plus inspecting page counts and encryption status. All work runs locally with no uploads, and every operation writes a new file beside the untouched original.

A sophisticated MCP server providing powerful file search capabilities including single file search, recursive directory search, and file information retrieval.

locidx

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

A server providing PDF form manipulation tools via MCP's API, allowing users to find PDFs across directories, extract form field information, and visualize form fields in documents.

A local MCP server for reading and editing Word (.docx) documents with 33 tools for content, formatting, comments, page layout, and track changes, running locally via stdio.

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 AI assistants to maintain persistent project context across sessions by storing and retrieving structured information in markdown files organized in a memory bank directory.

Enables MCP clients to render Markdown to HTML, estimate page counts, verify document delivery constraints, and atomically ship documents through a zero-dependency JSON-RPC stdio server.