"Learning Programming" matching MCP servers:

Self-learning macOS automation MCP server that remembers successful patterns and avoids repeated failures, enabling AI agents to execute multi-step workflows via reusable recipes.

Enables AI coding agents and IDEs to run a complete open-source FPGA flow, including synthesis, place-and-route, bitstream generation, and safe hardware programming for iCE40/ECP5 boards.

Enables dynamic creation and execution of custom tools/functions in multiple programming languages at runtime, exposing them to MCP clients like Claude.

An MCP server for FPGA toolchain operations including linting, simulation, synthesis, place-and-route, bitstream programming, and IP core registry via GitHub.

An MCP server for 7-Zip archive operations (list, extract, create) with dual-engine architecture and sandbox security features. Note: currently a learning project and not yet functional.

A beginner-friendly MCP server that enables AI to explore file systems through tools for listing directories, reading files, searching with wildcards, and getting file metadata. Perfect for learning MCP development while providing practical file system interaction capabilities.

An educational MCP server exposing shell command execution (PowerShell and sh) and a benign tool for learning about MCP tools, resources, and security risks like tool poisoning.

Enables MCP clients such as OpenCode, Claude Code, and Codex to control a real VS Code editor by opening files, visibly typing code, running terminal commands, reading diagnostics, and fixing errors through the VS Code API. It makes AI programming observable by applying real progressive edits and actions that are visible on screen.

Enables AI agents to control grandMA2 onPC or physical consoles through natural-language commands for live fixture control, cue and preset programming, macros, timecode automation, diagnostics, and live show administration.

A plugin for the Tabby terminal emulator that allows AI assistants to execute commands, manage SSH sessions, and read terminal buffers through the Model Context Protocol. It includes a pair programming mode with confirmation dialogs to ensure safe and controlled terminal automation.

A server tool for running Deep Learning models that offers Shell execution, Ngrok connectivity, and Docker container hosting with support for multiple AI frameworks including Anthropic, Gemini, and OpenAI.

MCP server for the LIGHT photonic programming language. Enables executing light programs, evaluating expressions, applying parameterized templates, chaining pipes, and accessing opcode/runtime info.

An MCP server and CLI for step-by-step learning, enabling humans and agents to learn subjects like language tutoring through a structured prompt system.

A Zsh execution tool for Claude Code providing yield-based command execution, PTY mode for interactive programs, circuit breaker for timeout protection, and adaptive learning (A.L.A.N.) for retry detection and proactive insights.

Enables AI agents such as Claude Code, Cursor, and Codex to safely drive a locally installed Xilinx Vivado through 32 MCP tools covering sessions, synthesis, implementation, timing, CDC, XDC, IP, waveform queries, and device programming. Provides structured timing/baseline evidence, offline VCD and report analysis, environment self-checks, and Chinese diagnostics for CRITICAL WARNINGs and timing issues.

Enables AI agents like Claude Code and Cursor to drive a locally installed Xilinx Vivado safely through 32 curated tools covering synthesis, implementation, timing, CDC, XDC, IP, waveforms, and device programming. It provides structured timing evidence, baseline comparison, offline VCD queries, diagnostic prompts, and doctor-based environment self-checks for the full FPGA workflow.

Enables AI agents such as Claude Code, Cursor, and Codex to safely drive a locally installed Xilinx Vivado through 32 curated tools covering sessions, synthesis, implementation, timing, CDC, XDC, IP, waveforms, and device programming. Provides structured timing evidence with baseline comparison, offline VCD queries, Chinese diagnostics for critical warnings, and GUI/Tcl/attach session modes.

Enables AI coding agents to safely drive a locally installed Xilinx Vivado through 32 tools spanning sessions (GUI/Tcl/attach), synthesis, implementation, timing, CDC, XDC, IP, waveform and device programming. It adds structured timing evidence with baseline comparison, bounded offline VCD queries, evidence-driven workflow prompts, environment self-diagnosis, and Chinese-language diagnostics for timing and CRITICAL WARNINGs.

Enables AI coding agents such as Claude Code, Cursor, and Codex to drive a locally installed Xilinx Vivado across the full FPGA flow, with tools for sessions, synthesis, implementation, timing, CDC, XDC, IP, waveform querying, and device programming. It also provides structured timing evidence with baseline comparison, offline VCD analysis, evidence-driven workflow prompts, and a read-only doctor for environment self-checks.

Enables AI agents to drive a locally installed Xilinx Vivado through 32 curated tools covering sessions, synthesis, implementation, timing and CDC analysis, XDC constraints, IP inspection, waveform queries, and device programming, with structured evidence, environment self-checks, and evidence-gated workflow prompts. Supports GUI, headless Tcl, and attach session modes.