llmaudit-mcp
llmaudit-mcp
llmaudit.app 的 MCP 服务器。它让任何人的助手都能在买家向 AI 询问推荐时,测量品牌是否会出现。
完整规格:specs/features/geo-13-mcp-server.md 位于私有仓库 llm-rank-tracker 中。
它暴露什么
start_visibility_check启动一次测量并返回一个runId。get_visibility_check获取测量结果。在提供商回复之前,返回running。llmaudit://methodology解释测量方式。
是两个工具,而不是一个,因为测量需要持续两分钟:audit 需要 15 到 60 秒,被测量的地图也是一样。
Related MCP server: ai-visibility-mcp
它返回什么,以及不返回什么
它返回 被测量的地图:实时查询的买家问题,以及每个回答对应谁。它绝不返回提供商的自我报告,也就是每个模型对品牌的自我认知。这两个数字在实际中差异很大,而自我报告总是更乐观的那个:因此该工具的契约不在任何字段中暴露它。
它从不返回 0-100 的评分:返回三档判定结果和次数统计。
费用
每次免费测量会消耗 llmaudit 的 API keys,大约 USD 0.05 到 0.15。有三个防护,全部通过测试验证:
每个域名每 30 天只能进行一次免费测量,该检查在调用 API 之前完成。
MCP_MONTHLY_RUN_LIMIT(默认 200)作为该渠道的月度上限,与 web funnel 的预算分开。生产环境中的 rate limit 按客户端身份进行,而非按此服务器的 IP(该 IP 在 serverless 中会轮换)。
环境变量
Variable | 用途 |
| API 的基础地址。默认 |
| 与 llm-rank-tracker 共享的密钥。没有它,生产环境按 IP 限制 |
| 表 |
| 该渠道的月度运行上限 |
开发
npm run dev # xmcp dev
npm test # vitest, sin red
npm run build # xmcp build测试在 fixtures/ 下运行,使用真实的测试装置(来自已付款探测的运行)。没有哪个测试会访问网络或调用任何提供商。
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