sample-lark-mcp-on-agentcore 是做什么的?
一个托管的远程MCP服务,让AI智能体能够操控飞书(Feishu/Lark),复用 lark-cli 的200多个工具和20多个技能。整个团队共享一个飞书应用,由IT部门集中管理;成员只需在浏览器中一次性授权,数据按用户隔离。基于AWS Bedrock AgentCore构建。
一个托管式远程MCP服务,让AI智能体操控飞书/Lark,复用lark-cli的200多个工具和20多个技能。团队共享一个飞书应用,由IT集中管理;成员在浏览器中一次性授权,数据按用户隔离。基于AWS Bedrock AgentCore构建。
该技能提供了一个托管式远程MCP(模型上下文协议)服务,使AI智能体能够无缝操作飞书(Feishu/Lark)平台。它复用了lark-cli的200多个工具和20多个技能,允许AI代理执行各种飞书任务,如消息发送、日历管理和文档操作。其核心优势在于团队管理:整个团队共享一个飞书应用,由IT部门集中管理,成员只需在浏览器中授权一次即可使用,且用户数据完全隔离,确保安全。该服务基于AWS Bedrock AgentCore构建,支持标准MCP协议,兼容Claude Code、Cursor和Codex等AI编码代理。对于需要将飞书功能集成到AI工作流中的开发团队来说,此项技能能够简化配置,降低授权开销,同时保持企业级的安全性和可管理性。部署后,团队无需为每个成员拥有单独的飞书应用,从而显著降低管理复杂度。
npx skills add aws-samples/sample-lark-mcp-on-agentcore一个托管的远程MCP服务,让AI智能体能够操控飞书(Feishu/Lark),复用 lark-cli 的200多个工具和20多个技能。整个团队共享一个飞书应用,由IT部门集中管理;成员只需在浏览器中一次性授权,数据按用户隔离。基于AWS Bedrock AgentCore构建。
Extract frames or short clips from videos using ffmpeg.
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Obra superpowers agent skills.
See, Understand, Act on video and audio. See- ingest from local files, URLs, RTSP/live feeds, or live record desktop; return realtime context and playable stream links. Understand- extract frames, build visual/semantic/temporal indexes, and search moments with timestamps and auto-clips. Act- transcode and normalize (codec, fps, resolution, aspect ratio), perform timeline edits (subtitles, text/image overlays, branding, audio overlays, dubbing, translation), generate media assets (image, audio...
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