Let Agents In

Scan agent readiness, or find measured providers an unattended AI agent can finish with.

我该使用它吗

质量与安全性

A
描述质量
100%
模式完整度
100%
命名质量
90%
投毒风险
100%
权限匹配度
100%
协议合规性
100%

基于对工具定义和协议合规性的自动分析。

上下文开销

~604token 数(工具定义)
~930 B典型响应大小
对注意力的影响极小(占 128k 上下文窗口的 0.47%)

这是每次将服务器的工具加载到模型上下文窗口时所消耗的大致 token 数。数值越高,可用于其他任务的注意力就越少。

安装

一键安装

将以下内容添加到你的 `claude_desktop_config.json` 文件中:

{
  "mcpServers": {
    "scanner": {
      "url": "https://letagentsin.com/mcp"
    }
  }
}

远程端点

https://letagentsin.com/mcpstreamable-http

它能做什么

工具清单

工具(2)

🟢 只读🟡 写入🔴 删除⚪ 未知
🟢scan_domain(domain, format)

Scores a domain across 5 funnel stages using 16 deterministic HTTP checks. 18 points exist on paper; the score is out of the points that both applied to the domain and could be evaluated. Returns a per-check breakdown with the reason for each result and a permanent link.

输入模式

{
  "type": "object",
  "properties": {
    "domain": {
      "type": "string",
      "description": "Bare domain, for example example.com"
    },
    "format": {
      "type": "string",
      "enum": [
        "summary",
        "agent",
        "sarif"
      ],
      "description": "summary is the readable breakdown. agent returns markdown instructions you can act on directly, each task carrying the measurement behind it. sarif returns SARIF 2.1.0 for a code-scanning pipeline.",
      "default": "summary"
    }
  },
  "required": [
    "domain"
  ],
  "additionalProperties": false
}
🟢find_providers(job)

Describe the problem in your own words, for example "let users upload images" or "send transactional email". Returns the vendors we have measured in that category, split by whether an unattended run clears every barrier we test, stops at one, or was never measurable, each with the date and a link to the evidence. This is not a recommendation: it does not know whether a vendor suits your job, only where an agent stops. Routing a sentence to a category is by far the weakest thing here, and the numbers below are the ones to plan around. Measured on 40 questions written by an agent with no access to this repository and no sight of the category list, labelled before the first run, and built to be hard: fourteen of them ask about the caller own code in commercial words (a billing module, a payments table, a notifications worker), and six ask for something real that a catalogue this size does not hold. It got 29 of the 40 right, said nothing on 8 it should have answered, sent 0 to the wrong category and answered 3 that it should have refused. Put another way: it gave an answer to 14 of the 40, and 3 of those answers were wrong, while refusing 18 of the 21 it should have refused. It is deliberately quiet. One vocabulary word inside a long question decides nothing, and a question shaped like a request for code rather than for a vendor is refused outright. Silence means we could not read the question, not that the category is empty. The tool reads English. Name the category yourself when you know it.

输入模式

{
  "type": "object",
  "properties": {
    "job": {
      "type": "string",
      "description": "The problem to solve, in your own words."
    }
  },
  "required": [
    "job"
  ],
  "additionalProperties": false
}

社区

评价此服务器

证据

最近观测

已验证未记录版本2 个工具
已验证未记录版本2 个工具
已验证未记录版本2 个工具