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Competitor ad research for AI agents: Meta Ad Library and TikTok ads, scored by hook and angle.
AdRadar 是 ChatHome Skills 收录的 MCP 条目，来源为 Official MCP Registry，质量分 78/100。 作为 Model Context Protocol 服务器，它向 Claude、Cursor、Copilot 等兼容 MCP 的 LLM 客户端暴露可直接调用的工具，让 agent 的能力超出模型内置范围。 该条目由 ChatHome Skills 的每日抓取从官方 registry 和 GitHub 发现查询中收录，每次运行都会重新核验仓库事实、新鲜度信号和安装元数据。 质量分综合了官方 registry 收录情况、可用安装命令、许可证完整性、仓库活跃度和 GitHub star 趋势，完整算法说明见来源页。安装命令已列于上方，可直接复制使用。 在将 AdRadar 加入生产 agent 工作流前，请核对上方的最近更新日期和仓库状态——下方事实快照是最近一次抓取的时点值。
mcp add io.github.Egggy1998/adradar https://adradarmcp.cloud/mcp运行此命令前，请先核对上游源码。
{
"_meta": {
"io.modelcontextprotocol.registry/official": {
"status": "active",
"isLatest": true,
"updatedAt": "2026-10-12T08:18:22.419166Z",
"publishedAt": "2026-10-12T08:18:22.419166Z",
"statusChangedAt": "2026-10-12T08:18:22.419166Z"
}
},
"server": {
"name": "io.github.Egggy1998/adradar",
"title": "AdRadar",
"$schema": "https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json",
"remotes": [
{
"url": "https://adradarmcp.cloud/mcp",
"type": "streamable-http",
"headers": [
{
"name": "Authorization",
"isSecret": true,
"isRequired": true,
"description": "Bearer <your AdRadar API key>. Get one at https://adradarmcp.cloud/en/pay"
}
]
}
],
"version": "2.0.0",
"repository": {
"url": "https://github.com/Egggy1998/adradar",
"source": "github"
},
"websiteUrl": "https://adradarmcp.cloud/en/",
"description": "Competitor ad research for AI agents: Meta Ad Library and TikTok ads, scored by hook and angle."
}
}