agentcheck

io.github.agentwares由 GitHub 账号 agentwares 发布v0.1.1更新于 Oct 27, 2026

Synthetic checks, nightly regression replay and model-drift alerts for AI agents

已验证Streamable HTTP可网页运行开发者工具安全与监控AI 与机器学习

概览

AI 生成的概览

agentcheck 的远程 MCP 服务器,让助手用合成检查、夜间回归回放和事件查询来监控 AI 智能体、MCP 服务器与 API。

可以做什么
  • 读取公开状态页与受监控目标:总体状态、正常运行时间、最近评分、未解决事件和徽章链接
  • 一次性预览任意公开的 Atlassian Statuspage 页面,含组件与未解决事件
  • 查询各厂商弃用页面上的模型退役与 API 版本停用信息
  • 登记监控目标(HTTP 端点、远程 MCP 服务器、A2A 智能体),添加检查并立即运行
  • 记录生产轨迹,把轨迹提升为可夜间回放的检查,并列出未解决与近期事件
  • 获取机器可读的套餐价格与附加项
适用场景
适合希望助手持续盯住 AI 智能体、MCP 服务器或 API 集成是否出现回归、模型或 API 弃用以及故障,并把真实生产轨迹转成定期检查的场景。只读工具无需账号即可查询状态和价格。
运行要求
以 Streamable HTTP 托管远程端点运行,无需本地安装。写入类工具需要 API 密钥,通过 Authorization 请求头以 Bearer 令牌发送,需在 agentcheck 控制台创建。状态与价格工具无需密钥。需要能访问 agentcheck 服务的网络。
安装前请注意
Authorization 请求头携带有效 API 密钥,请勿写入日志或共享配置。写入类工具会创建目标与检查、运行可能产生 LLM 评判费用的检查,并把生产提示、回答和工具调用记录到第三方服务。启用 rubric 或 baseline 评判及夜间回放前请先确认价格。

安装

在 SourceWeft 中

  1. 打开 控制台中的 agentcheck,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Web executable,通过 Streamable HTTP。 远程服务在工作区中配置后即可从网页运行时运行。

交给智能体安装

把这段提示词粘贴到 Claude Code、Codex、Cursor 等智能体,或 SourceWeft 对话中。智能体会读取该服务器的安装指南,先向你展示发布者、端点和登录方式,经你同意后再把它添加到你的客户端。密钥不会写进任何命令。

阅读 https://sourceweft.com/mcp/io.github.agentwares%2Fagentcheck/install.md,并按其中说明把这个 MCP 服务器接入我的客户端。修改任何配置之前,先告诉我它的发布者、端点和登录方式,等我确认。不要把 API 密钥写进命令或我会提交的文件;问我密钥应从哪里获取。

查看智能体所依据的安装指南

其他 MCP 客户端

把它添加到你客户端的 mcpServers 配置中。

{
  "mcpServers": {
    "agentcheck": {
      "type": "http",
      "url": "https://agentwares-agentcheck.vercel.app/api/mcp"
    }
  }
}

README

该仓库没有 README。

工具

11

agentcheck_get_status

Current status of a public monitored target: overall state, uptime over 24h/7d/30d, last check time, last nightly scores, open incidents and the badge/status URLs. Use the owner (GitHub login) and target slug from the status page URL https://agentwares-agentcheck.vercel.app/<owner>/<slug>. No API key needed.

输入参数slug必填owner必填

agentcheck_get_pricing

Machine-readable pricing for agentcheck: tiers with monthly USD price, target limits, check interval and features, plus per-run add-ons. Same data as /pricing.json. No API key needed.

无需输入参数。

agentcheck_model_retirements

Is this model retiring? Pass model IDs as your code or config names them (gpt-5-mini, claude-sonnet-4-5-20250929, gemini-2.5-flash, openai/o3-mini). For each, returns every announced shutdown on OpenAI's, Anthropic's and Google's own deprecation pages (OpenAI API, Claude API, Gemini API, Vertex AI): status, shutdown date, recommended replacement, the replacement's list-price ratio per token, the API changes the provider documents, the source URL with the date it was read, and a page with the details. retiring: false means no shutdown for that ID is on those pages. Language models only. No API key needed.

输入参数models必填

agentcheck_api_sunsets

When does the API version this code pins stop working, and what happens then? Pass provider and version pairs as your code pins them (shopify 2025-10, meta v21.0, google-ads v22, hubspot v1, twilio-flex 2.16.2, twilio-notify v1, keap xml-rpc, exchange-online ews, stripe 2024-06-20). For each, returns every dated end the provider's own versioning, changelog or retirement page lists: status, end date (and whether the provider gives only a month), what happens after it (error, silent fall-forward to another version, app delisting, or unsupported), whether the failure is silent, the replacement version, the source URL with the date it was read, and a page with the details. Where the provider's own pages give different dates for the same end, other_dates lists each one with its page and date_note says which the counts run to. A pair with no entry comes back with the reason: older than every listed version, no end date published yet, or a provider that publishes none (Stripe). Covers Shopify, HubSpot, Meta Graph and Marketing APIs, Google Ads and Content API for Shopping, Twilio Flex UI and Notify, Thryv's Keap XML-RPC, and Exchange Web Services (EWS) in Exchange Online. No API key needed.

输入参数pins必填

agentcheck_statuspage_preview

Read a public Atlassian Statuspage page once: its name, overall status, components (id, name, status, group) and unresolved incidents, from the page's own /api/v2/summary.json. Pass any address on the page: status.example.com, https://status.example.com/history or the JSON URL. Use it before POST /api/v1/statuspage, which turns the components you give a URL into a live agentcheck status page checked by agentcheck itself, with no signup; the answer carries that request's body. Same read as /statuspage/preview: only public addresses, 5-second timeout, 512 KB cap. Private pages cannot be read. No API key needed.

输入参数url必填

agentcheck_create_target

Enroll something to monitor: an http endpoint (JSON or OpenAI-style chat), a remote MCP server (Streamable HTTP url) or an A2A agent (origin with /.well-known/agent-card.json). Pass `checks` to create checks in the same call (POST /api/v1/probe proposes three). Returns the target id, the public status page, the badge SVG URL and a README snippet. The first check runs on the next scheduled tick, within five minutes; call agentcheck_run_now to run immediately. Free tier: 1 target, hourly; Starter+: 5-minute checks. Requires an API key.

输入参数urlauthkind必填nameslugalertschecksformatheadersisPublicmodelVarcorpusUrl另有 3 个

agentcheck_add_check

Add a check to one of your targets. A check runs an input (http path/prompt, mcp tool call, a2a message) on a schedule and judges the answer with a golden: exact, contains, regex and json_schema cost nothing; rubric and baseline use the LLM judge (baseline = same outcome as the last known-good answer). Returns the check id. Requires an API key.

输入参数kind必填name必填inputgolden必填targetId必填intervalSec

agentcheck_run_now

Run every check of one of your targets immediately (outside the schedule) and return pass/fail per check with latency, judge cost and any incident opened or closed. Use it right after enrolling, or to confirm a fix. Requires an API key.

输入参数targetId必填

agentcheck_record

Record one production interaction with your agent (the prompt or messages, the final answer, the tools it called, optionally the model) as a trace on a target. Call it from your agent or from a proxy in front of it after each task; promote a good trace with agentcheck_promote_trace to replay it nightly and catch regressions. Requires an API key.

输入参数nameinput必填modeloutput必填targetId必填toolCalls

agentcheck_promote_trace

Turn an imported or recorded trace into a replayable check whose golden is the recorded outcome (tool sequence + final-answer rubric). The check runs daily and in the nightly replay (Pro). Returns the check. Requires an API key.

输入参数traceId必填

agentcheck_list_incidents

Open and recent incidents across your targets (or one target): when they opened/closed, the failing check and the cause. Requires an API key.

输入参数targetId

版本历史

1
  1. v0.1.1最新Sep 16, 2026

评分

已满足适用检查项的 75%

该评分衡量此收录条目的完整程度,依据注册中心条目、端点与公开来源计算得出。它不是对服务器本身的评价,也不表示服务器安全或当前可用:可连通性是带日期的检查结果,评分也不包含安装量或用户评价。

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  • 描述必需15 分
  • 图标10 分
  • 文档15 分

    请声明包含 README 的 GitHub 仓库,或在 OAuth 受保护资源元数据中提供 resource_documentation。

  • 许可证10 分

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