Install and visualize graph-backed engineering intelligence skills, agents, and workflows for AI coding IDEs.
Intelligence pipeline for spec enrichment, complexity modeling, and pre-execution simulation
Scaffold a persistent engineering intelligence layer inside any software repository.
Advanced MCP server for security detections with Detection Engineering Intelligence, Knowledge Graph (Tribal Knowledge), Elicitation, and Resource Subscriptions
Connect to your Jellyfish Software Engineering Intelligence platform for comprehensive team insights, effort allocation, and delivery metrics.
Engineering intelligence layer for repositories - analyze impact, complexity, history, and enforce architectural invariants
Autonomous Engineering Intelligence Hub: bidirectional GitHub and Notion sync powered by Claude AI
MCP server for AI-powered engineering intelligence — standups, weekly reports, and sprint retrospectives
Software Engineering Intelligence MCP Server — 97% token reduction for Claude Code. 12 tools + 7 resources for scoped file discovery, flow summaries, bug tracing, planning, and multi-session memory.
A secure storage integration for redux-persist using Expo SecureStore. Powered by MEDHIRA - Engineering Intelligence Across Everything.
Enterprise governance framework for AI-assisted software delivery with Git hooks, SDD/OpenSpec, AST intelligence, evidence, MCP and multi-platform rule enforcement.
Document Intelligence Rest Client
Nexus CLI — Autonomous Engineering Intelligence from the terminal
An isomorphic client library for the Azure Document Intelligence service.
OCI NodeJS client for Threat Intelligence Service
A conversational AI-driven telecom multi-agent system for managing call balances, push notifications, marketing, targeting, and sales.
Google Cloud Video Intelligence API client for Node.js
Multi-channel AI gateway with extensible messaging integrations
Orchestrator daemon for dispatching coding agents to issues
Self-learning vector database for Node.js — hybrid search, Graph RAG, FlashAttention-3, HNSW, 50+ attention mechanisms
A JSON-driven UI engine for React Native and Expo that enables dynamic, runtime-rendered interfaces without rebuilding the app. Powered by MEDHIRA - Engineering Intelligence Across Everything.
Zep: Fast, scalable building blocks for production LLM apps
An online parser for GraphQL for use in syntax-highlighters and code intelligence tools
Typography assets for @ukic components
Opulent is an intelligent Templating Engine created to speed up web development through fast rendering and custom web component definitions.
Implementing the main engine and subroutines into a gem so I don't have to continuously recreate the wheel. Finally got the local subscriptions feed for rikusuto mode to work.
Simple, Regular Expression powered template engine. Intelligently handles HTML input.
A lita Image Search bot that returns the Image search results
Add intelligent to your Ruby engine
Maglev is a simple CMS mountable engine to quickly add intelligent pages to your site
Kalah is a Ruby based Kalah/Kalaha/Mancala engine. Useful for making intelligent game agents or interactive Kalah games. Flexible in terms of board structure.
RailsChatbot is a Rails engine that provides an intelligent chatbot system with knowledge base integration. It can answer questions about your application by indexing your models and content, using OpenAI's GPT models for intelligent responses.
ResilientLink delivers structured metadata from any URL with sub-second latency — Residential proxy infrastructure, intelligent caching, and an API engineered for enterprise scale.
RcrewAI Rails is a comprehensive Rails engine that brings AI agent orchestration to your Rails applications. Build intelligent AI crews that collaborate to solve complex tasks with full database persistence, background job integration, and a beautiful web dashboard for monitoring and management. Features: • ActiveRecord models for crews, agents, tasks, and executions with full persistence • Rails generators for scaffolding AI crews and agents • ActiveJob integration for asynchronous crew execution (works with any Rails background job adapter) • Web dashboard with real-time monitoring and management interface • Multi-LLM support: OpenAI GPT, Anthropic Claude, Google Gemini, Azure OpenAI, Ollama • Production-ready with logging, error handling, and security controls • Human-in-the-loop workflows with approval mechanisms • Tool ecosystem: web search, file operations, SQL, email, code execution
RSence is a different and unique development model and software frameworks designed first-hand for real-time web applications. RSence consists of separate, but tigtly integrated data- and user interface frameworks. RSence could be classified as a thin server - thick client system. Applications and submobules are installed as indepenent plugin bundles into the plugins folder of a RSence environment, which in itself is a self-contained bundle. A big part of RSence itself is implemented as shared plugin bundles. The user interface framework of RSence is implemented in high-level user interface widget classes. The widget classes share a common foundation API and access the browser's native API's using an abstracted event- and element layer, which provides exceptional cross-browser compatibility. The data framework of RSence is a event-driven system, which synchronized shared values between the client and server. It's like a realtime bidirectional form-submission engine that handles data changes intelligently. On the client, changed values trigger events on user interface widgets. On the server, changed values trigger events on value responder methods of server plugin modules. It doesn't matter if the change originates on client or server, it's all synchronized and propagated automatically. The server framework is implemented as a high-level, modular data-event-driven system, which handles delegation of tasks impossible to implement using a client-only approach. Client sessions are selectively connected to other client sessions and legacy back-ends via the server by using the data framework. The client is written in Javascript and the server is written in Ruby. The client also supports CoffeeScript for custom logic. In many cases, no custom client logic is needed; the user interfaces can be defined in tree-like data models. By default, the models are parsed from YAML files, and other structured data formats are possible, including XML, JSON, databases or any custom logic capable of producing similar objects. The server can connect to custom environments and legacy backends accessible on the server, including software written in other languages.
RSence is a different and unique development model and software frameworks designed first-hand for real-time web applications. RSence consists of separate, but tigtly integrated data- and user interface frameworks. RSence could be classified as a thin server - thick client system. Applications and submobules are installed as indepenent plugin bundles into the plugins folder of a RSence environment, which in itself is a self-contained bundle. A big part of RSence itself is implemented as shared plugin bundles. The user interface framework of RSence is implemented in high-level user interface widget classes. The widget classes share a common foundation API and access the browser's native API's using an abstracted event- and element layer, which provides exceptional cross-browser compatibility. The data framework of RSence is a event-driven system, which synchronized shared values between the client and server. It's like a realtime bidirectional form-submission engine that handles data changes intelligently. On the client, changed values trigger events on user interface widgets. On the server, changed values trigger events on value responder methods of server plugin modules. It doesn't matter if the change originates on client or server, it's all synchronized and propagated automatically. The server framework is implemented as a high-level, modular data-event-driven system, which handles delegation of tasks impossible to implement using a client-only approach. Client sessions are selectively connected to other client sessions and legacy back-ends via the server by using the data framework. The client is written in Javascript and the server is written in Ruby. The client also supports CoffeeScript for custom logic. In many cases, no custom client logic is needed; the user interfaces can be defined in tree-like data models. By default, the models are parsed from YAML files, and other structured data formats are possible, including XML, JSON, databases or any custom logic capable of producing similar objects. The server can connect to custom environments and legacy backends accessible on the server, including software written in other languages.
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