"Information about Tavily AI Search API" matching MCP servers:

A comprehensive MCP server with RESTful API that enables file operations, command execution, project management, and AI integration for remote development control with security features and real-time communication.

Pre-alpha P2P remote-control app with a local stdio MCP bridge for paired computers. Users build from source; platform support and host-side approvals apply.

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.

TaskFlow AI is a premium MCP Server designed for AI editors, offering 40+ built-in tools covering file system, HTTP requests, databases, Git operations, and more.

Multi-threaded terminal management MCP server for AI assistants, enabling async command execution, batch operations, and real-time web monitoring with up to 100 concurrent terminals.

MCP server that provides file operations and Moonshot API-powered tools (reasoning, code review, testing, research, web search, agent) for Kimi K2.5, requiring only a Moonshot API key.

Enables managing Linux hosts and local coding agents from an MCP client through shell commands, files, background jobs, system information, instruction and skill discovery, and optional Claude Code, Codex, or Cursor CLI conversations. It provides privileged remote access with token authentication and can run longer work in the background.

Provides a disposable, hardened Kali Linux sandbox with an MCP interface for LLM-driven security analysis of REST APIs, confining blast radius via container isolation.

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

Enables any MCP-compatible AI, whether in the browser or running locally, to create and edit projects, run terminal commands and long-running jobs, and optionally use Docker, all guarded by a policy engine, workspace jail, authentication, and audit logging.

Enables an AI agent to operate a spare Android phone through MCP: capture screenshots, inspect UI controls, tap/swipe, input Chinese text, launch apps, and optionally run rooted shell commands or transfer files. It also supports a live web console for remote viewing and control.

Enables AI agents to securely access authenticated services (HTTP, SSH, SMTP) without exposing secrets, by acting as a server-side proxy that injects authentication.

Local SSH credential broker and stdio MCP server that enables AI clients to perform SSH and SFTP operations via stable server_id aliases without exposing passwords, private keys, or passphrases.

Enables AI clients to securely operate a local machine via MCP or REST, providing file read/write, Playwright browser automation, and shell/service administration.

An MCP Server that enables natural language interaction with the Open Policy Agent REST API, allowing users to manage policies, decisions, and data through conversational interfaces.

An MCP (Multi-Agent Conversation Protocol) server that enables interaction with Google's Managed Service for Microsoft Active Directory through its OpenAPI, allowing users to manage identity resources through natural language.

MCP server that gives AI agents isolated, named Linux computers with stable IDs and lifecycle control. Supports multiple backends like Docker, Fly Machines, Modal, and E2B, with a dashboard for managing sandboxes.

Outbound-only remote shell, detached long-running jobs, and temporary file courier for AI agents. Hosted Streamable HTTP plus stdio via npx -y @aicommander/mcp.

Bridges Claude Desktop to local Windows 10 development environments to enable repository reading, documentation searching, and isolated code execution. It provides a secure interface for running allowlisted terminal commands and scripts directly through natural language.

ai-runtime-guard is an MCP server that sits between your AI agent and your system, enforcing a policy layer before any file or shell action takes effect. No retraining, no prompt engineering, no changes to your agent or workflow, just install, configure once, and your agent operates within the boundaries you set.