"Creative and simple use cases for MCP with SSE URLs" matching MCP servers:

Enables listing, retrieving, creating, and updating DMCA.com takedown, DIY, and compliance cases, plus fetching site reports, through the DMCA.com API with token authentication. It also supports minting an API token via login and returns upstream JSON responses as-is.

A local-only MCP server for AI video ad planning. It helps AI agents build video ad briefs, hooks, UGC scripts, storyboards, variation plans, script reviews, and AdsTurbo-ready prompts without calling AdsTurbo internal services.

Control a real iPhone or iOS Simulator through a macOS daemon and XCTest runner over USB or Wi-Fi: read screen text, tap, type, swipe, inspect logs and replay flows with explicit outcomes. Browser sandbox: use readonly to inspect 12 preloaded flows without a phone. Reuse an existing sandbox from MCP Deployments, or delete it before starting another. Device control needs your Mac and iPhone.

Runtime access for AI coding agents to observe and control Android and iOS apps.

Enables AI agents to see and drive Kasm Workspaces desktops by starting and stopping sessions, taking screenshots, and performing clicks, typing, key presses, and scrolling through MCP clients or as a native Hermes Agent plugin.

Let Claude Code, Codex and any AI agent use the Chrome you're already signed in to. Open-source CLI + MCP server + Chrome extension (native messaging, no debug port); stealth by default.

Enables Claude to see and control a real Android phone via MCP, reading the accessibility tree to tap, type, navigate, launch apps, and diagnose connectivity over ADB or cellular.

An open-source MCP server that lets any coding agent operate your computer like a person does—reading the UI through accessibility trees, clicking and typing in the background, showing an agent pointer, zooming into regions, and driving your signed-in Chrome on macOS, Windows, and Linux.

Odds are, most of what you want to build is already open source. Tell your AI agent what you're making, and it finds it: which repos to use as they are, which to adapt, and what's left for you to write. Every repo it names is real, licensed for your use or flagged, and checked live.

A Model Context Protocol (MCP) server for accessing Productive.io API endpoints (projects, tasks, comments, todos), tailored for read-only operations, providing streamlined access to essential data while minimizing token consumption

A Model Context Protocol (MCP) server for accessing Fathom AI API endpoints (meetings, recordings, transcripts, summaries, teams, team members) via GET operations.

Enables coding agents to ask what a window shows and receive a concise JSON answer from a local Ollama model instead of ingesting the full accessibility tree, reducing token usage. It is read-only and supports optional session context, health checks, and model release.

MCP server that recommends which npm/PyPI libraries to use or avoid, with concise verdicts, alternatives, and code snippets, keeping responses under 500 tokens.

An MCP server that allows checking local time on the client machine or current UTC time from an NTP server

Provides AI clients with deterministic Playwright-driven browser control, enabling navigation, interaction, screenshots, and inspection of rendered HTML, computed styles, console diagnostics, and font audits without an embedded LLM or API key.

Enables AI agents to search, filter, and monitor curated AI model API free credits and low-cost token promotions through eight tools, four resources, and three prompts — including finding deals expiring soon, checking eligibility and blocked conditions, and producing daily briefs.

Genpark-multivariate-ad-creative-fatigue-auditor

Enables Windows desktop automation via MCP, allowing AI agents to control mouse, keyboard, and screen capture with the same interface as Anthropic's computer-use tool.

Use Codex as a subagent inside Claude Code: async dispatch into a long-lived codex app-server, results pushed back into the Claude session automatically, steer/interrupt mid-task, and Codex's built-in code review.

Gives LLM agents spatial awareness inside Autodesk Maya, enabling scene inspection and measurement, aesthetic and engineering audits, camera planning, checkpoint/rollback safety, asset import, and viewport or render previews. Agents can also execute arbitrary Python in Maya to build and verify 3D scenes against engineering rules instead of writing blind.