AI Agents
babyagi
Yohei Nakajima's autonomous task agent - now a self-building agent framework in Python
★ 22.4k starsMIT
View guide →A Python framework for building MCP servers and agent tools.
arcade-mcp is an open-source ai agents project by ArcadeAI (ArcadeAI/arcade-mcp on GitHub). It has 1,047 GitHub stars and 119 forks, is released under the MIT license, and was last updated on GitHub on 7 October 2026.
Know what you want the agent to accomplish before touching any code.
Clone the repo and read the README's requirements section.
Install what's needed and add API keys or configuration.
Run the quickstart example, then iterate from there.
Servers without the boilerplate.
Focus on capabilities, not plumbing.
Secure your tools properly.
Claude, Codex, and other MCP clients.
The lingua franca of agent tooling.
Backed by Arcade's tooling work.
Download the source and move into the project folder.
git clone https://github.com/ArcadeAI/arcade-mcp.git
cd arcade-mcpIsolate dependencies, then install requirements.
python -m venv .venv && source .venv/bin/activate
pip install -r requirements.txtLaunch using the entry point shown in the README.
python -m arcade_mcp # check README for the exact commandIt is an open-source project at ArcadeAI/arcade-mcp with 119 forks. Check the contributors tab and recent commits to judge how active maintenance is.
Yes — it's MIT licensed: free to use, modify, and ship commercially. Just keep the license notice in copies.
MCP gives agents a standard way to discover and call tools; arcade-mcp is the scaffolding for building those servers in Python.
Developers whose agents need custom capabilities — internal APIs, proprietary data, special tools.
Clone the repo and follow the README quickstart — the docs at https://docs.arcade.dev walk through setup.
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