MCP Server2025
Centralized enterprise platform to manage org-wide MCP servers with a private MCP registry, security guardrails, cost controls, and observability. Offers a Kubernetes-native orchestrator, built-in RAG knowledge base, security sub-agents, and tools for governed AI adoption.
AI Infra2025
An open-source memory layer that turns agent runs and conversations into structured, persistent state recallable across sessions. Captures facts, events, preferences, and relationships automatically; LLM-agnostic with SDK and MCP integration.
AI Agent2025
Compiles an agent's raw chat logs, documents, and tool traces into three persistent layers — index, learned skills, and user memory — so context survives sessions. Claims 92% Locomo-benchmark accuracy and up to 95% lower token cost than replaying history.
AI Client2025
Indexes any repo into a knowledge graph of dependencies, call chains, and execution flows, then feeds it to AI coding agents via MCP so they stop missing context. Ships as a CLI plus a zero-install browser graph explorer with chat.
Seven-week course that builds a production RAG system from scratch — an arXiv paper assistant that starts with BM25 keyword search, then layers hybrid vector retrieval, local-LLM generation, Langfuse monitoring, and an agentic LangGraph Telegram bot.
AI Agent2025
Provides hierarchical, versioned semantic memory for AI agents with Git-like branching, commits, and rollbacks—using semantic paths and cryptographic provenance instead of opaque vector stores. Designed for branch-aware, auditable memory in multi-agent and production workflows.
AI Agent2025
Framework for building multi-modal AI agents that watch, listen, and reason over live video, pairing vision models (YOLO, Roboflow, Moondream) with LLMs like Gemini and OpenAI. Agents join calls in ~500ms and keep audio/video latency under 30ms.
Teaches AI agent principles and practice through a structured Chinese curriculum, pairing theory with runnable code so learners can build, debug, and extend agent systems step by step.
AI Agent2025
Open-source companion to a technical book that teaches how to design, evaluate and ship LLM-based AI agents — includes the full Chinese manuscript, community translations, chapter-aligned runnable example projects, and reproducible evaluation harnesses.
AI Agent2025
Audits source code for security flaws using LLM agents, then auto-generates and runs proof-of-concept exploits in Docker sandboxes to confirm which findings are real. Retrieves CWE/CVE knowledge via RAG; runs on hosted or local Ollama models.
AI Infra2025
Orchestrates multiple AI providers to generate context-aware attack payloads, scan web targets for 45+ vulnerability types, and produce compliance-mapped reports. Supports dynamic provider failover, RAG-indexed CVE intelligence, browser automation, and AI triage; requires API keys and authorized testing.