EvoMCP: Co-evolving MCP agents and training data
Supervised fine-tuning of Model Context Protocol (MCP) agents is typically conducted on a static data distribution, which fails to adapt to the student's evolving capabilities and leaves newly exposed weaknesses insufficiently addressed. To address these challenges, we propose \method, an agent--data mutual evolution f...
Xuan-Ang Gao, Ke-Peng Lin, Xin-Yan Shi et al.
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