"A server for enabling an AI agent to view and analyze video files" matching MCP servers:

MCP server enabling Claude Code to capture screenshots of Windows applications through WSL2, allowing AI to diagnose UI errors and verify layouts.

Provides agents with real Linux VMs to run commands, manage files, expose ports, and track costs, all through an ephemeral sandbox service.

MCP server that routes Claude Desktop chat into Claude Code, enabling headless execution and terminal handoff with session continuity.

Enables AI agents to invoke a local Stata installation, including a Windows Stata build under Wine on Linux and macOS, for regression analysis, econometrics, paper replication, and empirical research with command guards, resource monitoring, and automatic log capture.

Enables AI agents to securely connect to and manage remote servers via SSH, with tools for running commands, file operations, log inspection, service management, and system monitoring under configurable access controls and audit logging.

It enables AI assistants to run installed command-line tools and scripts, drive persistent terminals and browsers, and retrieve saved jobs, screenshots, and other evidence on a server. It also provides a dashboard for tracking sessions, installed tools, and connection settings.

Converts any Python Click or Typer CLI into an MCP server automatically — zero-code transformation that introspects CLI commands and exposes them as MCP tools.

A local MCP server that lets Hermes supervise Claude Code, delegating focused coding, research, or review tasks to the Claude Code CLI and managing worker sessions, background jobs, cancellations, and read-only reviews.

An MCP server that lets Claude query Google's Gemini CLI as a sub-agent. Get second opinions, verify information, and cross-reference answers between AI models.

Enables code execution in isolated Docker containers with persistent IPython, Node.js, or R kernels, supporting file import/export and cross-session transfers via MCP tools.

Enables any MCP client to execute DeepSeek Harness agents and shell commands through standard MCP tools, bridging multi-agent capabilities with sandboxed execution.

Provides workspace-scoped file operations and command execution tools for building Cursor-style agents, along with system prompts and tool definitions for LLM integration.

Delegates coding and read-only exploration tasks to the Antigravity CLI as blocking headless runs, mirroring live progress to on-disk stream transcripts and diffing git status to report touched files and out-of-scope edits. Supports resumable conversations, per-call model/agent/effort overrides, idle and hard timeouts, and discovery of available models and agent profiles.

An MCP server that exposes a sandboxed task runner protocol to any MCP client, enabling evidence-protected task execution, exit protocol reading, and autopsy reports.

Enables natural language SSH server management via Claude Code, allowing users to read logs, check services, run commands, and transfer files across multiple servers.

Encoding-aware, indentation-smart file tools for AI coding agents. 20+ tools including read/edit with automatic encoding detection, smart indentation conversion, SSH, SFTP, process management, and system utilities.

An MCP-only server that launches AI CLI tasks (Claude, Codex, Gemini, Forge, OpenCode) as background subprocesses and manages them via PID for status, output, and lifecycle control.

Enables running multiple AI CLI tools (Claude, Codex, Gemini, Forge, OpenCode) as background processes with automatic permission handling, allowing LLMs to execute async multitasking and combine different AI models.

Enables MCP-based communication with existing interactive terminal channels, such as shells or agent CLIs, by listing, reading, writing text, and sending control signals to tmux sessions without creating or managing them.

The Problem Modern distributed systems and AI agents require robust operational scaffolding. Simple CRUD apps or mock loops fail when subjected to real-world edge cases, asynchronous boundaries, and security constraints. The Solution An isolated execution platform for AI agents. An agent is given a broken service and a bounded toolset inside a disposable sandbox. Every command passes throug

Enables MCP clients to drive developer workflows through APIs and CLIs, with explicit workspace or trusted-workstation launch modes, bounded command previews, multi-repository rules discovery, and an on-demand skills/recipes entry point. It lets agents review changes, run commands, and load only the smallest relevant rule or skill while reporting evidence and unverified steps.

An AI-native Taskwarrior bridge that provides natural language task management for Claude Code and other AI systems, integrating with existing Taskwarrior infrastructure.

Discovery router for the agent-device CLI with status, install, help, prompts, and resources.

Enables ChatGPT to work directly on local projects by reading files, editing code, running tests and commands, inspecting Git state, and managing durable workflows, with optional delegation to local Codex agents for complex tasks.

An MCP execution layer that lets capable AI models safely control a developer workstation for file edits, terminal and process execution, Git operations, language-server analysis, browser and Windows UI automation, media processing, job/resource control, and checkpointing. It also coordinates durable single- or multi-agent tasks across providers with leases, dependency graphs, evidence logs, repair loops, and separate verification gates.

Enables n8n AI agents to manage MikroTik routers via SSH/SSE, providing tools for firewall, DNS, DHCP, WireGuard, interfaces, queues, backup, users, logs, and routes.

A download tool for AI agents that wraps aria2 with safety rules and MCP server support, enabling reliable downloads without false positives.

Exposes tools over stdio that let an AI agent create disposable Docker sandboxes to run commands and stream output, read and write files, and take snapshots, roll them back, fork them, list, and destroy them. It tells the model to snapshot before risky changes so failed attempts can be undone or explored in parallel on self-hosted infrastructure.

Enables AI clients to reuse local OpenSSH configuration for remote development and operations, providing command execution, file transfer and editing, search, synchronization, persistent terminals, background jobs, and TCP forwarding through 26 unified tools.

Creates and manages multi-agent teams of AI coding assistants (Claude Code, Codex CLI) that collaborate in tmux terminal sessions. Enables a leader agent to assign sub-tasks to team members for coordinated development.