AI Agents
arcade-mcp
A Python framework for building MCP servers and agent tools.
★ 1.0k starsMIT
View guide →Simple workflow patterns for building effective agents on MCP.
mcp-agent is an open-source ai agents project by lastmile-ai (lastmile-ai/mcp-agent on GitHub). It has 8,570 GitHub stars and 893 forks, is released under the Apache-2.0 license, and was last updated on GitHub on 25 January 2026.
Start with one concrete task rather than a grand architecture.
Clone the repo and check the examples folder for a quickstart.
Install packages, set environment variables, and point it at your model.
Execute the demo workflow, then adapt it to your own data.
Chains, routers, and orchestrators.
Tools come through the protocol.
Patterns, not a heavy framework.
Fits Python agent codebases.
Focused on what works.
Open and commercially friendly.
Download the source and move into the project folder.
git clone https://github.com/lastmile-ai/mcp-agent.git
cd mcp-agentCreate a virtual environment and install the requirements.
python -m venv .venv && source .venv/bin/activate
pip install -r requirements.txtTreat these as starting points - the README documents the exact commands.
python examples/quickstart.pylastmile-ai/mcp-agent is its home on GitHub, with 893 forks so far. The contributors tab and recent commits show how actively it is maintained.
Yes - it is Apache-2.0 licensed, so it is free for commercial use with attribution.
The code is free; you bring your own model provider, which may be a paid API or a local model.
mcp-agent is deliberately small - patterns over platform. If you outgrow it, graduate to a full framework; if you value simplicity, it may be all you need.
Follow the README quickstart, then browse the examples directory for patterns that match what you want to build.
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