diff --git a/upstream/ARUNAGIRINATHAN-K-awesome-ai-agents-2026/catalogue/README.md b/upstream/ARUNAGIRINATHAN-K-awesome-ai-agents-2026/catalogue/README.md index 3fde20e..ef1f9c1 100644 --- a/upstream/ARUNAGIRINATHAN-K-awesome-ai-agents-2026/catalogue/README.md +++ b/upstream/ARUNAGIRINATHAN-K-awesome-ai-agents-2026/catalogue/README.md @@ -2,9 +2,9 @@ title: "Awesome AI Agents 2026" task: "" lineage_type: import -upstream_source: https://github.com/ARUNAGIRINATHAN-K/awesome-ai-agents-2026/blob/cf7945ae/README.md -upstream_sha: cf7945ae -imported_at: 2026-07-02 +upstream_source: https://github.com/ARUNAGIRINATHAN-K/awesome-ai-agents-2026/blob/7abefb40/README.md +upstream_sha: 7abefb40 +imported_at: 2026-07-05 prompt_class: catalogue upstream_changes: accepted author: upstream @@ -155,6 +155,7 @@ validated: false - [Qdrant](https://github.com/qdrant/qdrant) `🌱` `[Rust]` `[Vector DB]` - High-performance vector similarity search engine with rich payload filtering for agent memory. - [RAGFlow](https://github.com/infiniflow/ragflow) `🌱` `[Python]` `[RAG]` - Open-source RAG engine with agent capabilities and deep document understanding for knowledge bases. - [SimpleMem](https://github.com/aiming-lab/SimpleMem) `🌱` `[Python]` `[Multimodal]` - Efficient lifelong memory for LLM agents supporting both text and multimodal inputs. +- [Superdense](https://github.com/Nimrobo/superdense) `🔬` `[TypeScript]` `[Memory]` - Gives coding agents persistent memory of what worked across sessions, tracked against real-world outcomes. - [Supermemory](https://github.com/supermemoryai/supermemory) `🌱` `[TypeScript]` `[Vector DB]` - Extremely fast and scalable memory engine and API designed for the AI era. - [Vestige](https://github.com/samvallad33/vestige) `🌱` `[Rust]` `[MCP]` - Provides local-first memory for coding agents with FSRS-6 retention, active forgetting, and correction tools. - [Weaviate](https://github.com/weaviate/weaviate) `🌱` `[Go]` `[Vector DB]` - Stores and searches vector embeddings with hybrid keyword and semantic retrieval for agent knowledge. @@ -748,6 +749,7 @@ Tools for running LLMs locally and self-hosting AI agent platforms with full pri - [LM Studio](https://lmstudio.ai) `🌱` `[TypeScript]` `[Local]` - Desktop application for running local LLMs with a polished UI across all major platforms. - [LocalAI](https://github.com/mudler/LocalAI) `🚀` `[Go]` `[OpenAI]` - Drop-in OpenAI API replacement that runs models locally without requiring a GPU. - [Ollama](https://github.com/ollama/ollama) `🚀` `[Go]` `[GitHub]` - Run LLMs locally with a dead-simple CLI interface and 162K+ GitHub stars. +- [RustFox](https://github.com/chinkan/RustFox) `🔬` `[Rust]` `[MCP]` - Self-hosted Telegram AI assistant written in Rust with sandboxed tool execution, MCP integration, and multi-agent orchestration. - [vLLM](https://github.com/vllm-project/vllm) `🚀` `[Python]` `[Local]` - High-throughput LLM serving engine with PagedAttention for production-grade local inference. - [Yao Agents](https://github.com/YaoApp/yao) `🌱` `[Go]` `[MCP]` - Local-first AI execution platform with Docker sandbox isolation, BYOK model configuration, MCP support, 5-stage Pipeline, and multi-platform messaging via WeChat, Feishu, DingTalk, Telegram, and Discord. @@ -767,6 +769,7 @@ Frameworks and tools for AI risk management, regulatory compliance, and governan AI agents specialized in penetration testing, vulnerability discovery, threat detection, and security analysis. +- [Dark-Moon](https://github.com/ASCIT31/Dark-Moon) `🌱` `[Python]` `[MCP]` - Autonomous AI penetration testing platform orchestrating 80+ offensive tools via MCP across web, cloud, Active Directory, Kubernetes, and API targets. - [Microsoft Security Copilot](https://www.microsoft.com/en-us/security/business/ai-machine-learning/microsoft-security-copilot) `🚀` `[Cloud]` `[Microsoft]` - Enterprise threat detection and incident response AI integrated across Microsoft security products. - [PentestGPT](https://github.com/GreyDGL/PentestGPT) `🌱` `[Python]` `[CLI]` - GPT-powered penetration testing tool with automated reasoning for vulnerability assessment. - [YAWNING TITAN](https://github.com/dstl/YAWNING-TITAN) `🌱` `[Python]` `[Graph-Based]` - Graph-based cybersecurity simulation environment for training and testing defensive AI agents.