"Information about Fetch function or service" 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.

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.

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

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.

Enables AI clients to search and read a local folder of notes, fetch public web pages as markdown with SSRF and robots.txt safeguards, and convert times between IANA timezones. It exposes these read-only capabilities as MCP tools over stdio or streamable HTTP.

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.

A minimal MCP server demo written without the MCP Python SDK that demonstrates the complete protocol flow. It provides weather, file search, and datetime tools, and includes a CLI client that bridges MCP tools with OpenAI function calling.

Enables AI agents to safely read, edit, and execute local Jupyter notebooks without running a separate service. Edits are guarded by compare-and-swap hashes and execution resumes or replays kernel state, so long-running cells aren't needlessly re-run.

A comprehensive Model Context Protocol server that enables AI assistants to interact with and manage Windows systems, providing capabilities for file system operations, process management, system information retrieval, registry operations, service management, network diagnostics, and performance monitoring.

Provides LLMs with safe, read-only access to local codebases for searching, reading files, and finding function definitions. All source code remains local, ensuring privacy while enabling AI assistants to explore project structures and functionality.

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 MCP clients such as Claude and Cursor to control an isolated cloud machine with a real browser, shell, filesystem, and web access, so agents can navigate pages, click and type, run commands, manage files, and search or fetch web content.

Enables Claude to read and analyze project schedule files in OmniPlan (.oplx) and Microsoft Project (.mpp) formats, answering questions about tasks, milestones, resources, and progress.

MCP server that allows AI agents to read, search, summarize, and answer questions about local PDF, DOCX, XLSX, and TXT files through five tools.

Enables natural-language queries about disk usage by driving WizTree scans and analyzing cached CSV snapshots. Users can find large files, duplicate data, folder breakdowns, and more without repeatedly rescanning the disk.

A redesigned Model Context Protocol server that enables AI models to access filesystems through privacy-preserving path aliases with an optimized 6-function API interface.