AIエージェント
arcade-mcp
A Python framework for building MCP servers and agent tools.
★ 1.0k スターMIT
ガイドを見る →babyagiは、yoheinakajimaが公開しているオープンソースのAIエージェントプロジェクトです（GitHub: yoheinakajima/babyagi）。GitHubスターは22,361、フォークは2,846で、MITライセンスの下で公開されています。GitHubでの最終更新は2026年1月31日です。
Yohei Nakajima's autonomous task agent - now a self-building agent framework in Python
Decide what you want the agent to accomplish and which functions it will need.
Install the babyagi package from PyPI, or clone the repository to explore the source.
pip install babyagi, then register functions and store any key dependencies (such as API keys) the functions need.
Execute a registered function, watch the execution log, and try the self-building agent flow.
Build agents by registering Python functions that the agent can call to complete objectives.
Organize related functions into packs - including code-writing and self-build packs - and load them into an agent.
Store secrets and dependencies from code or through the dashboard so functions can use them at runtime.
Ships a self_build flow where the agent processes user input and writes new functions for itself.
Runs functions in an environment with a log you can inspect from code or the dashboard.
Includes a dashboard for managing functions and key dependencies.
Get the source code from GitHub and enter the project directory.
git clone https://github.com/yoheinakajima/babyagi.git
cd babyagiBabyAGI is published on PyPI, so a virtual environment plus pip is all you need.
pip install babyagiThe README's Basic Usage shows registering functions - including ones with dependencies - and executing them.
import babyagi
# register your functions, then execute one - see README Basic UsageIt was created by Yohei Nakajima and is maintained as an open-source project on GitHub.
Yes - BabyAGI is released under the MIT License, so it is free to use and modify.
The framework itself is free, but functions that call an LLM need your own provider API key (for example OpenAI), and usage is billed by that provider.
Compared with larger frameworks like LangChain or AutoGPT-style platforms, BabyAGI is deliberately small and function-centric - easier to read end to end, with a self-building twist, but fewer built-in integrations.
Run pip install babyagi, follow the README's Quick Start to register a function, and execute it - then explore the dashboard and the self-building agent example.
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