ИИ-агенты
llm-wiki
Parallel multi-agent research that compiles wikis from any topic.
★ 1,4 тыс. звёздMIT
Смотреть руководство →iwe — проект с открытым исходным кодом из категории «ИИ-агенты» от iwe-org (iwe-org/iwe на GitHub). У него 1 748 звёзд на GitHub и 92 форка, он распространяется по лицензии Apache-2.0 и последний раз обновлялся на GitHub 4 октября 2026.
A markdown knowledge graph with LSP for editors and MCP for agents.
Get it from the official site.
Index a folder of markdown files.
Navigate the graph inside your editor.
Let AI agents query it over MCP.
Notes become a linked knowledge graph.
Graph navigation inside your editor.
Agents query your notes over MCP.
Your knowledge stays on your machine.
Fast indexing of big vaults.
Script graph queries from the shell.
Download the source and enter the folder.
git clone https://github.com/iwe-org/iwe.git
cd iweCompile the Rust binary.
cargo build --releasePoint it at a markdown folder.
./target/release/iwe index ~/notesA markdown knowledge graph with editor LSP and MCP memory for agents, at iwe-org/iwe.
Over MCP: they query your indexed notes as memory.
Yes. It is local-first.
Yes. Apache-2.0 licensed.
Any editor with LSP support; check the docs.
Parallel multi-agent research that compiles wikis from any topic.
Bring Claude Code, Codex, and Gemini CLI into Obsidian via Agent Client Protocol.
Ask questions of your Obsidian notes with private, local AI RAG.
Basic Memory: local-first MCP memory so you and your AI tools build a shared knowledge graph in Markdown
The open-source memory layer for autonomous agents — knowledge-graph memory that emulates human memory
High-performance code intelligence MCP server: your codebase as a persistent knowledge graph
Другие проекты из категории «ИИ-агенты» с наибольшим числом звёзд в каталоге LibreAI — реалистичный список альтернатив, если iwe вам не подходит.
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Соседние проекты из категории «ИИ-агенты» в каталоге, ближайшие по числу звёзд к iwe — продолжайте изучать полку по обе стороны от него.
Team memory for engineers and their AI agents.
Run context-engineering-kit locally: hand-crafted claude code skills focused on improvi...
Self-improving memory layer that works across AI agent harnesses.
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Retired agent framework: its prompts and guides live on in successor repos.
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Бесплатно и открыто — забирайте исходный код, ставьте звезду репозиторию и начинайте создавать.