by Agent-One-Lab · MCP Server · ★ 114
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🪽AgentFly: Training scalable LLM agents with RL (multi-turn, async tools/rewards, multimodal) <p align="
| Stars | 114 |
| Forks | 12 |
| Language | Python |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 36.7/100 |
| Open Issues | 1 |
| Last Updated | 2026-05-06 |
| Created | 2025-07-05 |
| Platforms | mcp, python |
| Est. Tokens | ~1388k |
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AgentFly is Scalable and extensible reinforcement learning for LM agents.. It is categorized as a MCP Server with 114 GitHub stars.
AgentFly is primarily written in Python. It covers topics such as agent, agent-rl, agentfly.
You can find installation instructions and usage details in the AgentFly GitHub repository at github.com/Agent-One-Lab/AgentFly. The project has 114 stars and 12 forks, indicating an active community.
AgentFly is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to AgentFly on Agent Skills Hub include Awesome-LLM-Papers-Comprehensive-Topics, Autono, SimpleLLMFunc. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.