"A search for information about the iPhone" matching MCP servers:

MCP server that drives Safari on a physically attached iPhone via Apple's safaridriver, enabling navigation, screenshots, DOM snapshots, console logs, network timings, and tap/type/scroll actions on the real device. No Xcode, Appium, or WebDriverAgent required.

Enables iPhone automation through Appium integration, allowing users to control apps, capture screenshots, interact with UI elements, and perform touch operations via natural language commands.

An MCP (Model Context Protocol) server that gives AI agents live, structured ad intelligence across Facebook, Google, and Instagram — data that no base model can produce from training alone. Powered by Apify actors. Works with any MCP-compatible client: Cursor, Claude, etc.

Enables AI agents to see and operate a real USB-connected iPhone from a Linux Docker host — taking screenshots with region zoom, reading the element tree, tapping, swiping, long-pressing, typing text, pressing hardware buttons, listing/launching/terminating apps, and opening URLs. Automatically recovers from replugs and crashes, re-signs its automation agent before expiry, and falls back to a signing-free HID path on newer iOS.

HandaaS的MCP服务器，提供全域资讯搜索、企业新闻、行业资讯、主题跟踪和企业动态监控能力，帮助用户开展行业研究和舆情分析。

Enables MCP clients like Claude to query Chinese A-share market data, including K-line charts with forward/backward adjustment, limit-up and limit-down pools, per-stock fund flows, index quotes, and stock news, with automatic symbol normalization and retry handling for throttled data sources.

Enables structured learning with a verified loop: define goals as observable claims, learn through teach-lab-test-gate per claim, and get independently graded by an adversarial examiner to ensure genuine progress.

Provides A-share (Chinese stock market) quantitative analysis through tools for stock screening, northbound capital flow tracking, dragon-tiger list analysis, margin trading, sector analysis, technical indicators, IPO info, and limit-up/down statistics using akshare data.

Enables Codex on Windows to manage iPhone/iCloud Reminders through a local MCP bridge, including listing, creating, updating, completing, and deleting reminders with due dates, notes, and priorities.

A-MEM is a self-evolving memory system for coding agents that automatically organizes knowledge into a Zettelkasten-style graph with dynamic relationships, enabling semantic and structural search.

Skill librarian for coding agents: describe a task and get the few matching skills from a large local skill collection, then report whether they worked. Runs locally with Ollama and SQLite.

Enables AI coding agents to request a second opinion from a different frontier model via a single tool call, with PII scrubbed before transit, live web search, and support for Claude, ChatGPT, Cursor, and Gemini.

提供A股实时行情、历史K线、财务报表、技术指标等全方位数据查询的MCP服务器，支持盘中即时更新及批量查询。

Enables an agent to submit a task brief and receive a short, validated list of skills from its full catalogue that are worth reading before starting.

Enables AI agents to request an independent second opinion from a different frontier model, with PII scrubbing before transit, live web search grounding, caching, and multi-provider failover.

This MCP server provides secure access to databases for AI agents, enforcing authentication, authorization, human approval, logging, and notifications to prevent dangerous actions.

Local MCP server for A-share stock trading via Tonghuashun, offering account/position queries, buy/sell/cancel orders with risk controls and forced user confirmation; currently simulated with a reserved interface for real broker channels.

Provides current weather information for any location and generates AI-powered responses using Google Gemini through FastMCP.

Enables broad web search for current, time-sensitive information, returning short title, URL, and snippet results rather than full pages. It supports region and result-count parameters through a keyless multi-engine backend.

MCP server for controlling satellite ground station operations in the Trench simulation, including pass management, downlink control, and antenna pointing.

An MCP server that enables AI agents to pause and request human approval or information via Slack, Telegram, or macOS dialogs before proceeding with actions.

Read-only MySQL MCP server that lets AI agents list tables, describe schemas, and run SELECT/SHOW/EXPLAIN queries with a row cap, bound to a single database for safety.

Provides a local MCP server for AI-powered web crawling on Windows, enabling agents to directly crawl and extract web content without requiring WSL.

Give any LLM agent a real Android or iPhone. 62 MCP tools: tap, swipe, type, screenshot, screen-tree reading, app launch, camera, TTS, crash reports, batched execution. Android via ADB, iPhone via WebDriverAgent, on-device inference, Docker+KVM emulators. Works with Claude Code, Cursor, LangChain, LlamaIndex, and any MCP client. MIT.

A Model Context Protocol server providing tools for querying A-share stock market data, including historical prices, financial reports, market indices, and macroeconomic indicators.

A local stdio MCP server that enables researchers to practice explaining their work outside a conference setting through a guided, one-question-at-a-time interview about their research, its audience, its consequences, and a concrete next step. It stores the saved answers in a local SQLite draft and returns an approximate rubric-based grade, without calling any model or requiring an API key.

Provides 11 composable MCP tools for A-share market research, covering quotes, news, technical signals, sector performance, portfolio risk, backtesting, and paper trading, with traceable data sources and calculation basis.

MCP server providing 29 A-share analysis skills including real-time data, capital flow, limit-up tracking, technical/fundamental analysis, backtesting, risk control, and Xueqiu portfolio tracking, enabling AI agents to execute market research and strategy tasks.

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

Enables LLM clients to access crop yield predictions from RGB imagery, topic-based PDF literature, and soil lab/moisture CSV data.