EvoScientist

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EvoScientist aims to harness vibe research by enabling self-evolving AI scientists that autonomously explore, generate insights, and iteratively improve. It is designed to be opinionated and ready to use out of the box, offering a living research system that grows alongside evolving agent skills, toolsets, and memory bases. Moving beyond traditional human-in-the-loop systems, EvoScientist adopts a human-on-the-loop paradigm, where AI acts as a research buddy that co-evolves with human researchers and internalizes scholarly taste and scientific judgment.

✨ Features

• 🤖 Multi-Agent Team — 6 sub-agents (plan, research, code, debug, analyze, write) working in concert.
• 🧠 Persistent Memory — Context, preferences, and findings survive across sessions.
• 🌐 Multi-Provider — Anthropic, OpenAI, Google, MiniMax, NVIDIA — one config to switch.
• 📱 Multi-Channel — CLI as the hub; Telegram, Slack, Feishu, WeChat, and more — one agent session.
• 🔬 Scientific Workflow — Intake → plan → execute → evaluate → write → verify.
• 🔄 Code Generation Modes — More Effort (iterative refinement), continuously improving code quality.
• ⚡ Adaptive Tools — Per-turn tool selection keeps only relevant tools visible, reducing noise.
• ✂️ Context Editing — Dynamic system prompt rewriting based on conversation state.
• 🔌 MCP & Skills — Plug in MCP servers or install skills from GitHub on the fly.

[!TIP] Looking for ready-to-use research skills? Check out — powered by 's engine and installable skills, the entire end-to-end research lifecycle is covered out of the box. are also compatible with other CLI coding agents.