Repository History
10 repositories tagged with AI Tools
AI Session Search: Ultra-Fast AI Agent Session Analysis
AI Session Search (aise) is an ultra-fast, Rust-powered tool designed for searching and analyzing local AI agent coding sessions. It seamlessly integrates and indexes nine different session formats, including those from Claude, Codex, Cursor, and Gemini CLI. This powerful utility enables developers to quickly recover context, track agent behavior, and efficiently manage their AI-generated code history.
oh-my-hermes: Enhance Hermes Agent with Advanced AI Workflow and Memory
oh-my-hermes is an all-in-one plugin designed to significantly enhance the Hermes Agent. It provides advanced coding intelligence, a robust long-term memory system, and optimized workflow packages, transforming standard Hermes requests into structured, actionable tasks with clear operational layers.
vibe-kanban-local: A Self-Contained Kanban for AI Coding Agents
vibe-kanban-local is a robust, local-only fork of the original BloopAI/vibe-kanban project, maintained after its upstream sunset. It provides a self-contained, single-user kanban board, allowing developers to integrate over ten different AI coding agents directly into their workflow without any cloud dependencies or logins. This tool is ideal for enhancing productivity with AI assistance in a private, offline environment.
Best of Agent Harnesses: A Curated List for AI Agent Development
RyanAlberts' Best of Agent Harnesses is a comprehensive, curated, and ranked list of over 100 AI agent harnesses and orchestration frameworks. It provides valuable insights for building reliable agentic systems, offering both human-readable guides and machine-readable formats for agents themselves. The repository is rescored weekly to ensure up-to-date recommendations.
product-manager-skills: AI-Powered PM Assistant for Coding Tools
The product-manager-skills repository transforms AI coding tools like Claude Code, Codex, Cursor, and Windsurf into a rigorous product manager. It enables AI to diagnose SaaS metrics, critique PRDs, plan roadmaps, run discovery, and provide career coaching for product professionals. This skill offers a structured, framework-driven approach to product management workflows, moving beyond generic AI responses.
MetaMCP: Unifying Model Context Protocol Servers with an All-in-One Gateway
MetaMCP is a powerful, self-hosted solution that acts as an aggregator, orchestrator, middleware, and gateway for Model Context Protocol (MCP) servers. It allows developers to dynamically combine multiple MCP servers into a single, unified endpoint, enhancing tool management and agent development. This TypeScript-based project simplifies the deployment and management of AI tools within a Dockerized environment.
Awesome Agent Almanac: A Curated List of AI Agents and Agentic Technology
Awesome Agent Almanac is a comprehensive awesome-list dedicated to AI agents, agent tools, MCP servers, and agentic technology. This community-curated resource provides an extensive collection of innovative projects in the rapidly evolving field of artificial intelligence agents, offering valuable insights for developers and researchers alike.
files-to-prompt: Concatenate Files into a Single Prompt for LLMs
files-to-prompt is a command-line tool designed to concatenate the contents of multiple files from a directory into a single, structured prompt suitable for Large Language Models (LLMs). It offers flexible options for filtering files by extension, ignoring patterns, and supports various output formats including standard text, Claude XML, and Markdown. This utility streamlines the process of preparing complex codebases or documentation for AI analysis.
AI Engineering Toolkit: 100+ Libraries for LLM Development
The AI Engineering Toolkit is a comprehensive, curated list featuring over 100 libraries and frameworks essential for AI engineers. It provides battle-tested tools, frameworks, and reference implementations to develop, deploy, and optimize applications built with Large Language Models. This resource aims to help engineers build better LLM apps faster, smarter, and production-ready.
Attachments: The Python Funnel for LLM Context and Multimodal Data
Attachments simplifies providing context to Large Language Models by transforming various file types into model-ready text and images. This Python library acts as a universal funnel, enabling developers to integrate diverse data sources like PDFs, images, web content, and even entire code repositories with just a few lines of code. It supports popular LLM APIs and frameworks, making multimodal AI development more accessible.