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Agent Seer is a pipeline that synthesizes realistic evaluation scenarios for AI agents from tool specifications without manual curation, improving tool-calling correctness and conversational coherence in multi-turn dialogues.
A developer created mcpgrade, a scoring tool for MCP servers, and found that a third of popular servers have poor documentation and usability for AI agents, with most errors from missing parameter descriptions.