"Building a Sequencer with Arduino in C++ and Enhancing Performance" matching MCP servers:

Enables AI clients to compile and upload Arduino sketches, manage boards, cores, and libraries via arduino-cli, scaffold projects, and read serial output over stdio.

A comprehensive Model Context Protocol (MCP) server for Arduino CLI interactions, built with FastMCP. This server enables AI agents to seamlessly interact with Arduino CLI for development, debugging, code verification, and more.

Enables AI assistants to compile, upload, and monitor Arduino boards via natural language, with electrical safety checks and dependency management.

Automates Arduino CLI workflows including dependency checks, compile/upload, serial monitoring, and safety preflight checks, all running locally on your machine.

Provides 12 tools to query South Korean building register data, including title sheets, floor details, and official house prices via the data.go.kr API. It enables users to perform smart building lookups and region code searches using natural language.

Call OpenAI Codex from Claude Code for independent second opinions, structured code review, and delegated coding tasks through a FastMCP plugin that drives the codex CLI safely.

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.

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 to manage a local Claude Code companion through MCP, implementing a dual-agent workflow where Codex handles reasoning and review while Claude Code performs engineering tasks.

Enables LLMs to read and write local user data, generate fake users via sampling, and interact with structured prompts and resources.

Enables users to describe their LLM fine-tuning job once and get the cheapest, fastest, and most balanced GPU options across a dozen cloud providers in seconds.

Enables academic research through paper search across multiple databases (IACR, CryptoBib, Crossref, Google Scholar), PDF processing, and GitHub repository browsing. Features modular architecture with FastMCP-based proxy server routing to specialized academic tools.

Relays a result screenshot to Slack so you can review a coding agent's output without opening the app.

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.

Gives AI assistants a genuine Borland Turbo C 3.0 toolchain via MCP, enabling compile and run of real 16-bit DOS C programs with diagnostics and classic examples.

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.

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.

An MCP server that enables LLMs to automate browser interactions using Playwright to fetch real-time Israeli weather data.

A minimal MCP server that exposes a run_command tool over stdio, enabling command execution within a Docker container.

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.