"MCP client for discovering and mapping active MCP servers" matching MCP servers:

SSH/SFTP server enabling remote command execution and secure file transfers, with integration for Claude AI.

A tool that helps manage and synchronize MCP server configurations across different AI assistant clients (Cline, Roo Code, WindSurf, Claude), automating the process of retrieving, listing, adding, and removing server configurations from client configuration files.

Streamlined MCP server with 8 essential tools for file operations, code editing, and command execution, covering 97.5% of actual workflow with minimal overhead.

50 tools and 400 functions for working with Excel/.xlsx spreadsheets — read/write, recalculate formulas, diff, repair broken references, and audit. Built for AI agents.

An MCP server that exposes macOS Spotlight search as tools, wrapping mdfind and mdls to provide full-text and metadata file search across the system.

Enables LLMs to securely SSH into remote servers, execute commands, and manage files via SFTP including listing, reading, writing, deleting, and renaming files.

A collection of small MCP servers for macOS automation that expose Apple Mail, MoneyMoney, and Spotlight functionality as tools via AppleScript and command-line, enabling AI applications to search mail, manage contacts and transactions, and perform system-wide file searches through natural language.

Enables AI agents to perform local video, audio, and file operations inside an isolated workspace, including cutting/concat videos, extracting audio, transcribing, and managing files, with typed responses and background job support.

MCP server that encapsulates Apple Mail on macOS via AppleScript, enabling invoice PDF search, attachment saving, and message flagging through natural language.

Enables MCP clients to discover OpenRouter image and video models, generate and edit images, create variations, launch and monitor video jobs, and save resulting media into authorized local project directories with cost controls.

A native Nextcloud app that exposes the instance as an MCP server so Claude and other MCP clients can read, search, and (with admin-granted permissions) edit files, notes, calendars, Deck cards, and Talk conversations. It runs inside Nextcloud with OAuth or app-password sign-in, applying each user's own Nextcloud permissions and admin-controlled per-operation grants.

Runs locally over stdio to read MSS54HP DME BIN images and Testo/TUNER drive logs, then proposes VE map and rf_korr corrections with evidence for each cell. Also reports what is in a BIN, whether its checksums are right, and why log samples were discarded.

Self-hosted MCP coding server and unified local Control Center for ChatGPT web, enabling file editing, command execution, Git operations, and optional upstream MCP tools with conversation access controls.

Enables users to safely read, write, edit, create directories, and list trees within a structured local Windows environment, with strict path validation and Git-based undo/version control.

MCP server for Obsidian vaults, optimised for Cursor agents — safe note editing, lean tool surface, direct filesystem access.

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.

TheWeave is a markdown-native memory architecture for Claude and any MCP-aware agent. Your agent's memory lives as plain .md files you own: a 5-verb MCP core over the vault, query-driven PageRank retrieval, bi-temporal facts (valid_from / valid_until), and a persona-as-vault model. No database and no embeddings server. The files are the memory, inspectable in your editor and versionable in git.

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

A FastAPI-based MCP server scaffold designed to extract material tables from AutoCAD DWG files. It enables users to automate CAD data processing by configuring drawing folder paths and layer-specific extraction parameters.

Enables document conversion between PDF, DOCX, and Markdown formats to facilitate reading and editing complex files in AI tools like Claude Desktop or Cursor. It utilizes marker-pdf and pandoc to provide structured text versions of documents, helping to manage context and support unsupported file types.

Read selected local folders from ChatGPT on macOS, with per-folder read-only or read-write access and hash-checked, recoverable edits. Requires local installation and a private ChatGPT app. The Glama container is a synthetic evaluation demo; it does not connect to files on your Mac.

An MCP server that grants AI agents unrestricted file system, Python, and PowerShell access on Windows for real, unfiltered automation.

An MCP server that enables secure terminal command execution, directory navigation, and file system operations through a standardized interface for LLMs.

MCP server to interact with Obsidian via the Local REST API community plugin.

A Model Context Protocol (MCP) server for ZeroDrive file management. It enables AI assistants like Claude to interact with ZeroDrive cloud storage through a standardized interface.

Enables Claude to interact with FTP servers through natural language commands, allowing users to list directories, download/upload files, create directories, and delete files/directories on FTP servers.

Enables AI clients to securely execute remote commands and transfer files over SSH through standardized MCP tools, with multi-host management, flexible authentication, and an admin console.

A Model Context Protocol server that provides seamless access to multiple storage services including S3, Azure Blob Storage, and Google Cloud Storage through Apache OpenDAL™.

Manages user data with resources, tools, and prompts for CRUD operations on a JSON file.

Implements the Model Context Protocol (MCP) to provide AI models with a standardized interface for connecting to external data sources and tools like file systems, databases, or APIs.