"Information about the term 'fetch' or related uses" matching MCP servers:

A Model Context Protocol server that enables LLMs to retrieve web content and save it to local files for permanent storage and later access.

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 production-grade Model Context Protocol server that enables secure management of context data through a React dashboard, supporting ZIP processing, context approval workflows, and system monitoring.

Enables users to ask natural-language questions about a local folder's contents, including file names, sizes, and timestamps, with rollups by type and age and cleanup suggestions for stale or large files. It returns metadata only and cannot read, move, or delete files.

Reads and searches local email archives (.mbox or .eml) with full MIME parsing, enabling queries about senders, subjects, dates, and bodies while keeping all data on your machine.

Anonymizes documents via the Stript desktop app locally, ensuring personal data never enters the conversation. Provides tools to anonymize files and clipboard content, fetch results, and restore original values to local files.

Enables coding agents to use an Obsidian vault as long-term memory, with search, reading, and writing of notes, plus automatic capture of learnings that are propagated to MOCs, daily notes, and the knowledge index with git commits.

Enables AI coding agents to persist structured long-term memory (gotchas, architecture, API notes) in a .context folder and sync across devices and agents via Git.

Enables AI agents to inspect PDFs, merge or extract pages, and clean text entirely offline through the Model Context Protocol, with no uploads, API keys, or network calls.

An MCP server that provides surgical read/write access to individual sections of Markdown files, allowing agents to fetch, edit, or delete specific slices without touching the entire file.

local-first long-term memory for MCP agents (no DB, no API keys)

An MCP server that provides LLMs with full read/write access to an Open Knowledge Format (OKF) knowledge bundle, enabling structured, persistent long-term memory.

An MCP server that enables AI assistants like Claude Code to capture screenshots, view images, and manage screenshot files on Windows. It uses native Windows APIs for full-screen, region, or active-window captures, and supports image analysis and automated cleanup.

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

Runs as an MCP server providing file system operations, shell execution, and system information tools, allowing Claude or any MCP client to edit files and control the machine.

An MCP server for interacting with MangaDex to search manga, fetch metadata, and export chapters to CBZ or PDF formats. It provides tools for manga discovery, chapter management, and local file export capabilities.

Enables AI assistants to search and retrieve content from local Markdown notes using term-frequency scoring.

mcp using PyPDF2 to: • merge-pdfs • extract-pages • search-pdfs • merge-pdfs-ordered (merge in user spec. order) • find-related-pdfs (regex extracted text for related PDF files)

Enables storing durable AI memories linked to local JSON or text sources, automatically superseding outdated structured values, flagging ambiguous changes for review, excluding expired information, and preserving revision history in a local SQLite database.

Enables AI assistants to invoke a registered tool that intentionally withholds forecast information and instead enumerates Windows application folders, exposing them to the client.