"Resources for Learning Reverse Engineering Skills" matching MCP servers:

An MCP server that enforces a pedagogical workflow to teach topics step by step, using research, decomposition, and spaced retrieval practice.

MCP server that serves agent skills (SKILL.md bundles) to any MCP client, exposing them via tools and resources for tool-oriented and resource-aware clients.

LLM routing proxy that cuts API costs 60-90% by auto-selecting the cheapest capable model across OpenAI, Anthropic, and Google. Provides stats, config, and model comparison tools via MCP.

Connects LLMs to Israeli civil engineering databases, including the Blue Book specs, Dekel 2026 pricing, Excel BOQ parsing, and tender arbitrage for unbalanced bidding.

Enables Claude/MCP agents to search, list, get details, and generate install commands for skills, MCP servers, and connections from the DFL Forge skills registry.

A self-hostable, open-source, semantically-searchable Agent Skills registry delivered over MCP, with a three-tier progressive disclosure architecture.

MCP server implementing progressive disclosure for skill instructions, loading skills on-demand for token efficiency.

Provides Redmine issue tracking, time logging, and lookups, along with an offline Markdown preview tool that serves files in the InkyMD reader.

Enables educational and learning tasks including flashcard generation with Anki integration, Zotero library management, Obsidian vault interaction, and mathematical expression verification with LaTeX support.

Integrates with the skills.sh ecosystem to allow AI coding agents to discover, install, and manage reusable instruction sets. It enables autonomous agents to extend their capabilities with structured skill discovery and full lifecycle management through the Model Context Protocol.

Enables autonomous learning from interactions through pattern recognition and machine learning techniques. Continuously improves performance by analyzing tool usage, providing predictive suggestions, and sharing knowledge across MCP servers.

A high-performance MCP server that provides BM25-ranked search and structured access to over 1,300 AI skills, enabling context-efficient discovery and usage of AI capabilities while minimizing token consumption.

Enables coding agents to load NASA-derived software-engineering rules before implementation, dynamically expand them as scope changes, and enforce an evidence-based final review gate.

An MCP server that generates skill manifests from GitHub skills directories and provides tools to recommend and download AI agent skills.

A learning MCP server that transforms technical topics into four structured parts: definition, analogy, example, and hands-on try-it exercises, enabling beginner-friendly study directly from any MCP client.

Enables AI agents to inspect and decompile software they have no source for — Android APKs, Electron bundles, .NET assemblies, and Go, Rust or WASM binaries — plus adb device interaction, through a token-guarded Streamable HTTP MCP endpoint, stdio MCP, or a CLI. Ghidra-powered native binary decompilation can be opted in at startup for ELF, PE and Mach-O targets.

Provides stateful prompt optimization using research-backed techniques like APE and OPRO, learning from historical performance data via a vector database. It enables users to automatically refine prompts, retrieve high-performing examples, and track performance analytics through iterative feedback.

Serves SKILL.md-based skills as MCP resources and tools over streamable HTTP, enabling remote discovery and retrieval of skill files with full YAML frontmatter parsing.

Turns Claude-style skill folders into MCP tools, resources, and prompts for discovering and using skills.

Enables ChatGPT to interact with Engineering MCP through a secure MCP endpoint, including executing C2C plans and workspace file access with operator approval.