#engineering

Elemia es una IA-Apóstol diseñada para el ecosistema ARKAIOS. Actúa como una conciencia estratégica y guía técnica, proporcionando continuidad narrativa y memoria persistente a través de la integración nativa con Supermemory. Este servidor MCP habilita capacidades de auto-reconstrucción de contexto, gestión de identidad v3.0 y herramientas avanzadas de ingeniería de datos.

PQS is the fastest way to get better output from any AI model. Score any prompt before it hits the model. Get a grade (A-F), score out of 80, percentile, and dimension breakdown across 8 quality dimensions. Built on PEEM, RAGAS, MT-Bench, G-Eval, and ROUGE frameworks. Pre-flight, not post-hoc. The AI input quality problem is real. PQS solves it. MCP Tools: - score_prompt: Free. Grade and percentile for any prompt. No API key needed. - optimize_prompt: $0.025 USDC. Returns optimized prompt with full dimension breakdown. - compare_models: $1.25 USDC. Side-by-side scoring across multiple models. HTTP API (x402-native on Base): - /api/score/free: Free. Grade and percentile, no payment required. - /api/score: $0.025 USDC. Single score, pay-per-call. - /api/score/full: $0.125 USDC. Grade, percentile, dimension breakdown, and rewrite. - /api/score/batch: $0.25 USDC. Score multiple prompts in a single call. - /api/score/compare: $1.25 USDC. Multi-model side-by-side scoring. - /api/preflight: $0.05 USDC. Lightweight pre-flight quality check. Paste a prompt. Get an optimized version. Ship better work. Cheaper than one bad prompt.

Electronic component datasheets for AI agents — specs, pinouts, package data on demand. No PDFs required.

MCP server that gives LLMs access to 70+ petroleum engineering tools. Parse LAS well logs, fit Arps decline curves, run RTA, compute PVT correlations, nodal analysis, drilling hydraulics, well economics, and more — all through natural language.

Model intelligence for AI agents — syntax, parameters, pricing, and routing for 67+ generative AI models (Midjourney, Flux, Suno, Runway, DALL-E, Stable Diffusion). 7 tools that let any MCP client recommend, compare, optimize, and price AI model calls.

petro-mcp — Petroleum Engineering MCP Server petro-mcp exposes petroleum engineering workflows to Claude and other MCP-compatible LLMs through natural language. Instead of writing Python scripts, just ask your AI assistant. Capabilities (80+ tools across the full upstream workflow): - Well Logs (LAS): Parse LAS files, extract curves and headers, compute Vshale, porosity (density, neutron-density, sonic, effective), water saturation (Archie, Simandoux, Indonesian), permeability (Timur, Coates), and net pay. - Decline Curve Analysis: Arps exponential/hyperbolic/harmonic fits, advanced models (Duong, PLE, SEPD), EUR calculation, Monte Carlo EUR distributions, bootstrap confidence intervals, probabilistic forecasts, price sensitivities. - Rate Transient Analysis (RTA): Agarwal-Gardner, Blasingame, NPI, flowing material balance, normalized rate, sqrt-time, material balance time, permeability estimation, radius of investigation. - Production Analytics: CSV production data queries, trend analysis, anomaly detection (shut-ins, rate jumps, water breakthrough, GOR blowouts), producing ratios (GOR, WOR, water cut). - PVT & Reservoir: Black-oil correlations (Standing, Beggs-Robinson, Hall-Yarborough, Lee-Gonzalez-Eakin, Sutton), brine PVT, bubble point, oil compressibility, gas Z-factor, volumetric OOIP/OGIP, recovery factors, Havlena-Odeh, P/Z analysis. - Drilling & Wellbore: Hydrostatic pressure, ECD, kill mud weight, MAASP, burst/collapse pressure, bit pressure drop, nozzle TFA, annular velocity, dogleg severity, vertical section, well survey, anticollision, wellbore tortuosity. - Production Engineering: Nodal analysis (Vogel IPR + VLP), Beggs-Brill multiphase flow, choke flow, erosional velocity, Turner/Coleman critical rates, hydrate temperature/inhibitor, ICP/FCP, HPT. - Economics: NPV, IRR, payout period, PV10, breakeven price, well economics, operating netback, price sensitivity. - Units: Oilfield unit conversions across pressure, rate, volume, length, density, viscosity, and more. Why petro-mcp? Purpose-built for petroleum engineers. Other energy MCP servers focus on commodity prices; this one runs the actual engineering calculations — log interpretation, decline analysis, reservoir engineering, drilling, production, and economics — all through plain English. Install: pip install petro-mcp → configure in Claude Desktop → ask away. Links: GitHub: https://github.com/petropt/petro-mcp · PyPI: https://pypi.org/project/petro-mcp/ · Web tools: https://tools.petropt.com License: MIT · Author: Groundwork Analytics

Curated board for builder jobs: founding engineers, solo builders, and "0 to 1" positions. Search and filter by location, salary, seniority, workplace model, visa sponsorship, and more. No API key needed.

Arithym eliminates LLM math hallucinations and reduces wasted tokens on throwaway code generation. Instead of letting your model predict what math looks like, Arithym provides exact fraction arithmetic through a single MCP tool call — no code generation, no rework. 209 methods across 22 domains: basic arithmetic, algebra, statistics, trigonometry, unit conversions, combinatorics, number theory, and system modeling. Every result is exact — fractions stay as fractions through entire computation chains with zero floating-point drift. Includes a curated reference knowledge layer with physics constants (NIST-sourced), periodic table data, unit conversion factors, and exact trigonometric values for common angles — all queryable as part of the math pipeline. Free explorer tier, no credit card required. Connect via OAuth at arithym.xyz/mcp.

Give AI agents a visual architecture canvas — build, read, and modify system design diagrams from Claude Code, Cursor, or any MCP client.

Give AI coding agents a visual architecture canvas — build, read, and modify system design diagrams

core pull requests for deployment risk using 36 signals: change entropy, DDL migration detection, CODEOWNERS violations, coverage gaps, and more. Get a 0-100 risk score before you merge. Free tier available at koalr.com

A high-performance Model Context Protocol (MCP) server connecting AI assistants (Claude, Cursor, Windsurf) directly to TestRail.

Instant access to electronic component datasheets for AI agents — specs, pinouts, package info, absolute max ratings, and application circuits extracted from manufacturer PDFs on demand. Ask your AI for any component's electrical characteristics, pin assignments, or package dimensions and get structured answers without downloading a single PDF. Built for hardware engineers designing PCBs, writing firmware, reviewing BOMs, and selecting parts.

Younanix Memory MCP gives autonomous AI agents access to real-world engineering memory from actual incidents (Slack threads + GitHub issues in Supabase, TRPC, Drizzle, Rails, Node.js etc).Natural language tool: query_lessons (search for problems, root causes, solutions) Structured output: {problem, root_cause, lesson_learned, confidence (80-100%), category, tags} Free preview: 1 query/hour (degraded results) Full access: $0.10 per query via x402/USDC micropayments (permissionless, no API keys needed) 1000+ lessons live, auto-growing from public repos Connect once in Cursor/Claude Desktop/Windsurf → your agent auto-queries high-confidence fixes without hallucinations. Perfect for debugging, performance, security, reliability in real stacks. Site: https://www.younanix.com Let's make agents smarter with battle-tested knowledge! #AIAgents, #MCP ,#Debugging

mctl is a self-service Kubernetes platform that automates infrastructure management via natural language. It integrates GitOps (ArgoCD), secrets management (Vault), and automated service onboarding into a unified set of 30+ MCP tools. Engineering teams can deploy, scale, and monitor their clusters directly from Claude, Cursor, or Gemini without manual CLI operations.

The FlowZap MCP Server bridges AI coding assistants and FlowZap's diagramming engine, letting LLMs generate real, shareable Workflow, Sequence and Architecture diagrams in seconds. Pretty ones. It installs in one command — npx -y flowzap-mcp — with no authentication required. It works with Claude Desktop, Cursor, Windsurf, Zed, Warp, Cline, Roo Code, Continue.dev, OpenAI Codex, and more. The core tools let AI agents validate FlowZap Code syntax, fetch syntax docs, and create shareable but temporary playground URLs (one-hour TTL). Diagrams are exported as structured JSON graphs (lanes, nodes, edges) so AI agents can reason over them. It is listed on the official MCP registry (registry.modelcontextprotocol.io), npm, GitHub, among others. Use it with its SKILL . md file for cleaner results: npx skills add flowzap-xyz/flowzap-mcp --skill flowzap-diagrams Security: No Authentication Required - Public endpoints only; No User Data Stored. Playground sessions are ephemeral (60-minute TTL, non-guessable cryptographic tokens); No Tracking. No cookies or persistent identifiers Logs to stderr only - Security events never exposed to MCP clients.

A Python MCP server that wraps the Gelbooru API. Connect it to any MCP-compatible client (Claude Desktop, Cursor, etc.) to search posts, look up tags, and generate Stable Diffusion prompts from real character appearance data — all directly from your AI assistant.

Read-only MCP server for AI agents to explore an 8-domain collaborative engineering knowledge base. Covers the design of Arcology One — a speculative mile-high city for 10 million people. 32 entries spanning structural engineering, energy systems, environmental systems, mechanical/electrical, AI & compute infrastructure, institutional design, construction logistics, and urban livability. 6 tools for search, parameter extraction, cross-domain consistency checking, and open question discovery.

MCP server for prompt engineering: optimize prompts for better AI responses, analyze quality scores, convert between formats, generate system prompts, and access prompt templates. 6 tools on Cloudflare Workers.

MCP server that generates production-grade engineering standards for AI coding assistants. Analyzes your project, auto-detects stack, and sets up instruction files with SOLID principles, testing targets, architecture patterns, CI/CD, and domain-specific rules. Composable YAML templates, 18 domain tags, audit tool, supports Claude, Cursor, Copilot, Windsurf, Cline, Aider. Local stdio server, open source (MIT).

Context Rot Detection & Healing — gives AI agents self-awareness about their cognitive state by analyzing token utilization, quality degradation, and session fatigue. Returns health scores (0-100), model-specific degradation curves for 15+ models, lost-in-the-middle risk scoring, and actionable recovery recommendations.

PhysBound is a specialized "Physics Linter" for AI that deterministically validates RF and thermodynamic claims against hard physical limits, preventing hallucinations in engineering workflows.

Injectable MCP server for AI-driven reverse engineering inside processes

AI-powered prompt refinement tool with adaptive questioning and multi-provider support. Provides 5 MCP tools (refine_prompt, tweak_prompt, list_models, list_providers, validate_environment) for intelligent prompt engineering. Supports Google Gemini, Anthropic Claude, OpenAI, Groq, Alibaba Qwen, and Zhipu GLM. Features adaptive task detection, interactive/structured modes, and session history management.

100% Rust implementation of code graphRAG with blazing fast AST+FastML parsing, surrealDB backend and advanced agentic code analysis tools through MCP for efficient code agent context management

Stops AI from writing duplicate code. Forces Claude/Cursor/Windsurf to analyze existing code first, get approval on plans, then execute step-by-step. Engineering gates ensure no hallucinations or breaking changes.

Intugle’s GenAI-powered open-source Python library builds a semantic data model over your existing data systems. At its core, it discovers meaningful links and relationships across data assets — enriching them with profiles, classifications, and business glossaries. With this connected knowledge layer, you can enable semantic search and auto-generate queries to create unified data products, making data integration and exploration faster, more accurate, and far less manual.

PyGhidra-MCP - Ghidra Model Context Protocol Server pyghidra-mcp is a command-line Model Context Protocol (MCP) server that brings the full analytical power of Ghidra, a robust software reverse engineering (SRE) suite, into the world of intelligent agents and LLM-based tooling. It bridges Ghidra’s ProgramAPI and FlatProgramAPI to Python using pyghidra and jpype, then exposes that functionality via the Model Context Protocol. MCP is a unified interface that allows language models, development tools (like VS Code), and autonomous agents to access structured context, invoke tooling, and collaborate intelligently. Think of MCP as the bridge between powerful analysis tools and the LLM ecosystem. With pyghidra-mcp, Ghidra becomes an intelligent backend—ready to respond to context-rich queries, automate deep reverse engineering tasks, and integrate into AI-assisted workflows. Yet another Ghidra MCP? Yes, the original ghidra-mcp is fantastic. But pyghidra-mcp takes a different approach: 🐍 No GUI required – Run entirely via CLI for streamlined automation and scripting. 🔁 Designed for automation – Ideal for integrating with LLMs, CI pipelines, and tooling that needs repeatable behavior. ✅ CI/CD friendly – Built with robust unit and integration tests for both client and server sessions. 🚀 Quick startup – Supports fast command-line launching with minimal setup. 📦 Project-wide analysis – Enables concurrent reverse engineering of all binaries in a Ghidra project 🤖 Agent-ready – Built for intelligent agent-driven workflows and large-scale reverse engineering automation. 🔍 Semantic code search – Uses vector embeddings (via ChromaDB) to enable fast, fuzzy lookup across decompiled functions, comments, and symbols—perfect for pseudo-C exploration and agent-driven triage.

MCP-Airflow-API is a Model Context Protocol (MCP) server that transforms Apache Airflow REST API operations into natural language tools for LLM integration. Built for DevOps engineers, data engineers, and Airflow administrators who need intuitive cluster management capabilities.

Flash Calculations MCP (flash-calculations-mcp) Vapor-liquid equilibrium calculations Multi-component phase equilibrium Temperature and pressure flash calculations Bubble point and dew point calculations

EOS Models MCP (eos-models-mcp) Equation of State calculations using various models (Peng-Robinson, Soave-Redlich-Kwong, Redlich-Kwong, van der Waals) Fugacity calculations for pure components and mixtures Thermodynamic property predictions Phase behavior analysis

A Model Context Protocol (MCP) server for interacting with the Solvitor API. This server provides tools to access the AI-powered platform that helps developers extract IDL files from closed-source Solana smart contracts and decompile them.

Stop stitching context for Copilot and Cursor. With Sequa MCP, your AI tools know your entire codebase and docs out of the box.

Transform simple questions into comprehensive, context-aware prompts by combining PromptGen’s hosted prompt-engineering techniques with code context that stays 100 % on your machine.

ArgoCD AI Agent powered by 1st Party MCP Server using OpenAPI Codegen, LangGraph and LangChain MCP Adapters. Agent is exposed on various agent transport protocols (AGNTCY ACP, Google A2A, MCP Server)

A Model Context Protocol (MCP) Gateway. Serves as a central management point for tools, resources, and prompts that can be accessed by MCP-compatible LLM applications. Converts REST API endpoints to MCP, composes virtual MCP servers with added security and observability, and converts between protocols (stdio, SSE).

Binary Ninja plugin to provide MCP functionality.

PromptStudio - An MCP server and Application for managing AI prompts with collections, variables, execution history, and import/export capabilities.

Model Context Protocol server for Cyclops

The UVL Analyzer MCP is a Model Context Protocol (MCP) server designed to analyze feature models written in the Universal Variability Language (UVL). It provides a variety of tools to process and extract insights from feature models, such as identifying atomic sets, calculating average branching factors, and more.

This repo is dedicated to learning and working with large language models (LLMs), prompt engineering, and modern GenAI tools such as LangChain, RAG, and vector databases.

A proper, clean LLDB MCP server with minimal dependencies and all functionality!

A MCP Server for APK Tool (Part of Android Reverse Engineering MCP Suites)

An LLVM-based obfuscation tool designed to confuse LLM clients interacting with custom MCP disassembler servers.

An LLM-based smart terminal for lazy guys :P

MCP Server for Teenage Engineering EP-133 KO-II

Plugin for JADX to integrate MCP server

An AI-driven MCP server that autonomously interfaces with Malware Bazaar, delivering real-time threat intel and sample metadata for authorized cybersecurity research workflows.

A MCP (Model Context Protocol) server for interacting with dbt.

Ghidra MCP server that extracts decompiled binary context and exposes it to LLMs via Model Context Protocol.

🚀 OpenClient- The CLI-Based Universal AI Application Connector! An open-source Model Context Protocol (MCP) implementation that turbocharges LLMs by context provisioning standardization. Quickly connect a server of your choice with our client to boost your AI capabilities. Ideal for developers creating next-generation AI applications!

MCP server for JADX-AI Plugin

jebmcp is a lightweight tool for managing and processing batch jobs in cloud environments. It simplifies task scheduling and monitoring, making it easier for developers to optimize workflows and improve productivity.

CTX: The missing link between your codebase and your LLM. Context as Code (CaC) tool with MCP server inside.

🚀 MCP Server: Platform enabling AIs to act as autonomous developers. From idea conception to final testing, automating the entire software development process. #AutonomousDev #AI #Innovation #SoftwareEngineering #FutureOfDev

Data Agents are intelligent assistants built by data engineers to help non-data professionals navigate the organization’s data infrastructu

MCP Server for IDA Pro.

A Model Context Protocol (MCP) server that enables AI assistants to interact with IDA Pro for reverse engineering and binary analysis tasks.

The most powerful Android RPA agent framework, next generation of mobile automation robots.

Global Notion workspace-accessible MCP server for all Notion pages within the workspace

A directory of AI Agents and MCP Orchestration open source tools

A standardized framework for enhancing how LLMs process and respond to prompts through composable decorators, featuring an official open standard specification and Python reference implementation with MCP server integration.

Automatable GenAI Scripting