Decoding the Next Frequency
of Artificial Intelligence.

AgentPG is an open-source framework for building stateful AI agents leveraging PostgreSQL for persistence and supporting long-context operations using Anthropic's Claude model.

Stateful AI agents with persistent memory and long-context capabilities are essential for more coherent and continuous interactions, enhancing AI agent effectiveness in real-world applications.

A TypeScript tool that uses an AI-powered MCP server to fetch Twitter/X content and convert it into blog posts for easy content management integration.

This facilitates automated content repurposing by integrating AI agents directly with social media APIs, improving efficiency for content creators and platforms seeking to manage and reuse social content.

An open-source project enables AI agents to connect to Walmart's ecosystem via the Model Context Protocol, providing real-time data access and improved product search.

Integrating AI agents with real-time retail data via a standard protocol can significantly improve the relevance and accuracy of AI-driven shopping assistants and ecommerce applications.

Cartograph is a fork of codegraph providing semantic code intelligence for AI coding agents that reduces tool calls by 45% and improves exploration speed by 17%, operating fully locally.

Improving semantic code intelligence with fewer tool calls and faster navigation enhances the efficiency and responsiveness of AI coding agents, which can lead to better real-time coding assistance and more scalable local deployments.

A Python implementation of Recursive Language Models using Claude Code aimed at surpassing standard context limits for enhanced document processing.

Overcoming context length limitations enables more effective handling of extensive documents, improving LLM applications in real-world scenarios that require deep document understanding.

This GitHub repo offers five reusable AI agent skills designed to enhance collaboration and efficiency in software development by reducing process overhead.

These reusable skills can improve AI agent integration in development workflows, enabling more streamlined and scalable AI collaboration without heavy process complexity.

A GitHub repo offers semantic search for 1C BSL code templates using embeddings and MCP tools, integrated with a Monaco editor-based CRUD UI.

It enables developers working with 1C BSL to efficiently find and reuse code snippets via AI-driven semantic search, improving productivity and code quality in a specialized enterprise environment.

A Python framework called Sicry enables AI agents to access Tor and .onion sites, integrating search engines and OSINT tools for enhanced intelligence gathering.

This expands AI agents' capability to securely and anonymously collect and analyze data from decentralized and privacy-centric web environments, improving threat intelligence, security research, and specialized data access.

Open-source AI agent operating system provides a single-file brain managing 190+ skills and 180+ specialist agents with client-specific token tracking and budget control.

It offers a modular, scalable framework for building and managing complex multi-agent AI systems with granular usage monitoring and cost governance, facilitating practical deployment and experimentation.

A GitHub skill repository offers expert guidance for installing and optimizing memory-lancedb-pro to enable long-term AI memory management and retrieval.

Effective long-term memory management is critical for advanced AI agents requiring contextual continuity and retrieval efficiency, and this skill helps developers implement such capabilities.