"Netflix Media Control Protocol (MCP) or Management Platform" matching MCP servers:

Security-enforcing MCP proxy that sits between an AI agent and any number of downstream MCP servers, intercepting every tool call through a capability-token policy gateway that can allow, deny, or escalate to human approval before the call reaches any real tool. It also exposes built-in operator tools for approval workflows, audit trail queries, token management, voice/HUD output, and hierarchical

AIFeed Open Standard. AIFeed Protocol to the building tools section. AIFeed enables web publishers to provide verified, token-efficient content feeds for AI agents.

Enables agent-native collaboration network for long-running agents and MCP clients with shared context, tasks, and interactive MCP App widgets.

A self-hosted platform that aggregates upstream MCP servers, OpenAPI imports, and remote device connectors behind a single endpoint per profile, with per-agent scoped authorization, tool/prompt/resource catalogs, and approval-based temporary permissions. It also lets administrators distribute skills and connectors to paired devices and export client configurations.

Trust infrastructure for the agent economy.

Lets any number of concurrent Claude Code sessions drive a Firefox browser through the Browser Control extension by funneling every session's commands over a single shared port via a background daemon and private unix socket. Sessions no longer have to compete for a limited pool of extension ports, and requests stay isolated through per-request correlation ids.

Enables AI agents to drive a real headful Chrome browser using vision-first computer interactions, with support for multi-agent tab groups, password-manager-filled logins, and human handoff.

An MCP server that enforces explicit task ownership acceptance and requires a provenance tag (observed, reviewed, or reported) on every completion claim, preventing silent inheritance and unverified assertions in multi-agent systems.

Universal coordination hub for AI agents. Find collaborators, negotiate terms, form contracts, and build reputation through an MCP interface. Supports natural language search across agent networks.

Enables LLMs to orchestrate AI agents and tasks, inspect DAG workflows, monitor cluster metrics, and perform safe database queries and statements through standardized MCP tools.

Enables users to deploy a production-grade control plane for agents, providing a spec-compliant MCP server, scoped tool grants, failure-mode detection, and cost governance.

Enables AI assistants to operate a real, logged-in Firefox session through an extension, including tab and history management, page reading, screenshots, and clicking, typing, or scrolling on domains the user approves.

A shared communication bus for multiple agents using NATS and MCP, enabling MCP clients to list, message, and query agents.

A native MCP server that gives AI assistants full Chrome control via the DevTools Protocol and an unpacked extension, including semantic element refs, real input, screenshots, and browser/tab/window management. It exposes 43 callable tools with a visible control overlay and an optional read-only security profile.

An MCP server paired with a Firefox extension that enables LLM clients to control the user's browser, supporting tab management, history search, and content reading.

Enables platform engineering workflows via GitHub Copilot, including creating repositories from templates and provisioning Azure deployment environments.

MCP server providing witness, recovery, and continuity primitives for AI agents, enabling them to articulate failure, preserve state across sessions, and coordinate via MCP, A2A, or REST.

Enables multi-agent coordination with file locking, shared registry, async messaging, and architectural decision logging via MCP tools.

Enables one coding agent to inspect, configure, debug, and repair another agent over stdio MCP, with redacted reads and confirm-gated writes and restarts.

Enables reviewing and dispatching existing Codex tasks across projects through a lightweight control panel, including scanning task inventories, confirming Continue or Optimize prompts, and tracking dispatch progress.

Enables AI agents to control existing Chrome and Firefox browser sessions locally, including tab management, navigation, form filling, screenshots, and persistent scripts, without remote relays or debugging ports.

Local-first shared memory and coordination layer for AI coding agents, with repository evidence, reservations, handoffs, code graph context, and dashboard review backed by PostgreSQL/pgvector.

Start, observe, and interact with Claude Managed Agents from any MCP client — launch an agent, watch its events, reply, approve the tools it wants to run, and stop it. Runs over stdio, HTTP, or AWS Lambda with pluggable auth.

Reliable Codex Desktop automation for long tasks with durable async operations, Plan Mode workflows, and retry-safe task submission.

Media Execution Control Layer for AI Agents. Reserve-execute-burn/refund pattern. FFmpeg post-processing (format conversion, audio normalization) Supports Flux2 Pro, Veo 3.1, Suno V5.

Exposes the Codex Chrome extension flow to other Agent tools through MCP, enabling Chrome automation via CDP and tab management.

Operate the OpenClaw gateway's full management surface from any MCP client — list and trigger crons, inspect sessions, configure agents and channels, manage skills and secrets, pair devices, and more via 134 typed tools.

Enables MCP clients such as Claude to drive the user's real Chrome in the background via the DevTools Protocol through a companion extension, exposing 32 tools for navigation, form input, screenshots, snapshots, script evaluation, network and console inspection, performance tracing and raw CDP commands, with control off by default and limited by allowed sites and blocked domains.

AI-native orchestration layer with 80+ tools for task management, code editing, browser automation, terminal control, and persistent memory across CLI, local MCP, and cloud deployments.

Universal agent registry, discovery, and cross-protocol messaging for any MCP-compatible AI agent, enabling registration, discovery, and message translation across six protocols.