"Using Ghidra for Reverse Engineering and Decompiling Software" matching MCP servers:

Model Context Protocol server for Ghidra reverse engineering. 179 tools for decompilation, symbol management, cross-references, and binary analysis.

Enables MCP clients to execute Python snippets and interact with Ghidra through its PyGhidra scripting environment via a local Java plugin.

A sandboxed MCP tool for reverse engineering that provides a unified interface to various reverse engineering tools with security restrictions.

Enables AI agents and automation to perform Ghidra reverse-engineering tasks through MCP, including decompilation, live debugging, P-code emulation, data-flow analysis, and headless script execution, with specialized AArch64-aware emulation.

MCP server that enables AI coding assistants to audit repositories against engineering rules, generating self-contained HTML reports with citations and optional GitHub issue filing.

Provides software design guidance via MCP, including SOLID principles, design patterns, pattern scaffolding, and heuristic code-smell detection to help review and refactor code.

Lets AI agents gate actions before they happen with allow/ask/deny verdicts, rank up to 255 options, and report decision stats.

An MCP server that facilitates interactive software development planning by breaking down projects into manageable tasks, tracking progress, and saving implementation plans.

An anti-detection browser MCP server designed for JavaScript reverse engineering through the Camoufox engine. It enables AI assistants to perform dynamic debugging, function hooking, and network interception while bypassing sophisticated bot detection mechanisms.

Enables converting software development requirements into traceable estimates, WBS breakdowns, PERT calculations, risk registers, roadmaps, quotations, and professional PDF proposals or action plans. It supports reviewing assumptions, exclusions, scope gaps, and commercial documentation before sending deliverables to clients.

Automates Cole Medin's context engineering methodology to generate high-quality Product Requirements Prompts (PRPs) by analyzing existing codebases, asking contextual questions, and synthesizing insights.

Enables local and offline XLSX header cataloging, candidate relationship inference, and Oracle SELECT/WITH SQL generation without accessing databases or executing SQL.

A Chinese-friendly, locally running MCP server for WeChat Mini Program engineering, helping developers break down ideas into actionable tasks, inspect projects, generate blueprints, and perform security scans.

Enables AI clients to investigate data engineering workflows by exposing tools for job status, logs, schema lookup, read-only SQL, and searching documentation/incidents, along with resources and prompts for ETL failure analysis.

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

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

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.

Analyzes code repositories and generates comprehensive documentation published to Google Docs with Mermaid diagrams.

Enables MCP-compatible agents to perform read-only inspection of OpenPLC Editor projects, including retrieving project structure and listing programs, function blocks, and functions.

Enables AI agents to perform local video, audio, and file operations inside an isolated workspace, including cutting/concat videos, extracting audio, transcribing, and managing files, with typed responses and background job support.