LangChat 是Java&LangChain4j生态的开源 AI Agent 应用平台，支持多模型、Agent、知识库 RAG、Skills、MCP 与智能问数。

Official DESIGN.md files published by companies themselves. First-party design systems that AI agents read to generate consistent UI.

A compendium drawn from real commercial projects and hundreds of thousands of lines of AI‑assisted code. Read it end‑to‑end or feed this repo to your AI agent for summaries and Q&A. Stars and watches appreciated! ⭐

GenBI (Generative BI) for AI agents, an open-source, governed text-to-SQL through an open context layer that turns natural-language questions into trusted dashboards, charts, and SQL across 20+ data sources, such as BigQuery, Snowflake, PostgreSQL, ClickHouse, Amazon Redshift, Databricks and more.

The ultimate RAG for your monorepo. Query, understand, and edit multi-language codebases with the power of AI and knowledge graphs

Adaptive Python web scraping toolkit + MCP server for AI agents. Self-healing selectors that survive site changes, TLS-fingerprint stealth to bypass anti-bot filters, CSS/XPath parsing, and 24 built-in scrapers, clean, structured, LLM-ready data from any URL.

🪁 A lightweight, modern Kubernetes dashboard. All your clusters. One workspace.

Sandbox your local AI agents so they can read/write only what they need

660+ muapi-hosted generative-media models plus community-submitted third-party API tools (SEO, enrichment, social, scraping) — one YAML file per entry, browsable by capability.

Generate "Rules for AI". Quickly ✨

The Fastest AI Memory Model - Your Second Brain

Hermes Atlas — the decision layer for Hermes Agent: install guidance, mode & skill picks, and a curated catalog of 240+ ecosystem tools with live GitHub data

Turn your workday into structured workflows agents can execute. 100% local, served over MCP.

Open-Source Personal Cloud OS for Always-On Agents

The retrieval layer for production AI systems. Lightning-fast (<10ms) search without vector databases. Built for browser, edge, on-device, and cloud.

Let your agents read, send, and react to email autonomously, without human involvement

Version control for AI agents — track what your agent did, blame any line to a prompt, inspect any step.

📚 从零开始构建大模型

Embeddable vector database for Go with Chroma-like interface and zero third-party dependencies. In-memory with optional persistence.

Meet Mitsu, your chibi red-team operator. Connect your AI provider, set the scope, and she can take an authorized pentest from recon and attack-surface mapping through vulnerability discovery, > exploitation, and post-exploitation, armored with 165+ MCP-connected tools and live session intel. Guide every step or let her pwn autonomously. ( ◠‿◠)