도구

Personalized tutoring system from HKU's HKUDS: build a knowledge base from textbooks for Q&A, step-by-step solutions and quizzes, for teachers and self-learners. The deeptutor command outputs JSON for agents like Claude Code. Needs Python 3.11+, Node.js 20+ and an LLM API key.

Runs the cognee memory engine as an MCP server whose remember, recall and forget tools write documents and conversations into a knowledge graph and vector store for cross-session retrieval. Start it with Docker or uv first; needs an LLM API key by default, or connect to Cognee Cloud.

Writes conversations and business data into Graphiti's temporal knowledge graph so agents can retrieve long-term memory by entity, fact and time. Open source from Zep; start FalkorDB or Neo4j and the server with Docker first, and configure an LLM API key.

Turns an Obsidian vault into a local-first knowledge base: imports sources into interlinked notes with citations, answers questions from what is already in the vault, and adds 15 skills including search, vault health checks and Canvas knowledge graphs.

Stores agent memory as local Markdown notes that both people and AI can read, write, search and link, and you can open them directly in Obsidian. Local-first, open source and free, with a paid cloud sync option.

Learns your domain and working style over a few rounds of conversation, then generates a personalized Markdown knowledge system (folders, note templates, processing pipelines, hooks and maps) so agents remember knowledge across sessions. First setup takes about 20 minutes and is token-heavy.

Self-hostable long-term memory for agents, offering MCP, a REST API and a web dashboard: semantic search, knowledge graph and automatic memory consolidation. Embeddings are computed locally; choose SQLite, Cloudflare or Milvus as the backend.