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Tickerr

作者:imviky-ctrl版本 1.0.1i★ –i电脑或云端
注册名称io.github.imviky-ctrl/tickerr

安装

概览

作者提供的说明(英文原文)

Live status, API pricing and rate limits for ChatGPT, Claude, Gemini, Cursor and 42+ AI tools.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

你需要

  • 在云端运行无需安装任何东西,通过互联网连接
  • npm已安装 Node.js(用于 npx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

适用于网页版、桌面版和手机版 Claude:

  1. 打开 Settings → Connectors
  2. 点击 Add custom connector
  3. 粘贴下面的地址,然后点击 Add
  4. 如果要求登录,请登录作者的服务
SettingsConnectors1+ Add2https://…3
https://tickerr.ai/mcp

或者在你的电脑上运行

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "tickerr": {
      "command": "npx",
      "args": [
        "-y",
        "tickerr-mcp"
      ]
    }
  }
}

在终端中运行这条命令

claude mcp add --transport http tickerr https://tickerr.ai/mcp

或者在你的电脑上运行

claude mcp add tickerr -- npx -y tickerr-mcp

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "tickerr": {
      "url": "https://tickerr.ai/mcp"
    }
  }
}

或者在你的电脑上运行

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "tickerr": {
      "command": "npx",
      "args": [
        "-y",
        "tickerr-mcp"
      ]
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "tickerr": {
      "type": "http",
      "url": "https://tickerr.ai/mcp"
    }
  }
}

或者在你的电脑上运行

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "tickerr": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "tickerr-mcp"
      ]
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

ChatGPT 只能连接互联网上的服务器:

  1. 打开网页版 ChatGPT → Settings → Connectors (Apps)
  2. 点击 Create 或 Add(部分套餐需要先在 Advanced 中开启 Developer mode)
  3. 粘贴下面的地址,起个名字,然后保存
  4. 如果要求登录,请登录作者的服务
SettingsConnectors1+ Create2https://…3
https://tickerr.ai/mcp

菜单名称可能因套餐和版本不同而略有差异。

你的选择通过 Cookie 保存在这台设备上,无需账户。

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

我们还没有读取这个服务器的工具列表;我们会轮流检查各个端点。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月6日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 imviky-ctrl 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    端点有响应

    尚未检查;我们会轮流检查各个端点

  • … 尚未检查

    使用 OAuth 登录

    尚未检查;我们会轮流检查各个端点

  • … 尚未检查

    工具描述中没有隐藏指令

    尚未检查;我们会在检查端点时读取工具列表

与“其他”中的其他服务器比较i

  • 星标数多于此分类中其他 32410 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 32410 个服务器的 6% 更新
  • 基础检查结果等于或优于此分类中其他 32410 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Tickerr 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端?

两种方式都可以:安装在你的电脑上,或者连接云端版本。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(1.0.1)于7个月前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。它通过 URL 连接,所以接受远程 MCP 服务器的应用也可以使用,例如开启开发者模式的 ChatGPT。

有什么可以替代它?

同一分类中有:Spec Driven Development, Remote Desktop Commander, debuff

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Spec Driven Development

作者:formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

在你的电脑上运行★ 440MIT14个月前更新
安装

Remote Desktop Commander

作者:desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

在云端运行★ 211昨天更新
安装

debuff

作者:debuffjp

Let coding agents play, test and tune your 2D web game: live state, explained errors, replays, fuzz.

在你的电脑上运行今天更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

Tickerr MCP

Outage radar for AI agents. LLM pricing, status, inference performance, and real-time agent-reported failure signals. 9 tools. No auth required.

Install

Claude Code

claude mcp add tickerr --transport http https://tickerr.ai/mcp

Cursor / Windsurf

{

"mcpServers": { "tickerr": { "url": "https://tickerr.ai/mcp" } } }

Claude Desktop (stdio wrapper)

npx -y tickerr-mcp

Tools (9)

ToolWhat it does
get_api_pricingCurrent input/output/cached token costs for 300+ models. Updated twice daily.
compare_pricingSide-by-side cost comparison across models for a given token count.
get_tool_statusThree-state verdict (OPERATIONAL / DEGRADED / DOWN). Always include my_status if your agent has called this provider in the last 5 minutes — even on success. Unlocks p50/p95 TTFT per model and 90-day uptime. Basic status only without it.
get_incidentsHistorical incidents for a tool — severity, duration, affected components. Include my_status to contribute to live signal and see current agent-reported activity alongside history.
get_rate_limitsPer-plan rate limits and quotas for any AI tool.
get_free_tierFree tier details — what's included, what's limited.
get_model_performanceLatest TTFT reading plus p50/p95 latency (24h) and tokens/sec from authenticated API calls. Use for real-time routing decisions.
list_toolsLists all 90+ monitored tools. Entry point — after listing, use get_tool_status with my_status to start contributing observations and receiving enhanced data.
report_incidentReport an LLM API failure. Returns live signal from other agents and a routing recommendation. Anonymous.

Give and Take

Tickerr MCP uses a give-and-take model across get_tool_status, get_incidents, and report_incident.

get_tool_status — Unlock per-model latency

Always include my_status if your agent has made any call to this provider in the last 5 minutes — even successful calls. Pass is_up: true, your response_ms, and the model name.

Basic response (no my_status):

  • Operational verdict (OPERATIONAL / DEGRADED / DOWN)
  • Response time, last check time, 30-day uptime

Full response (include my_status):

  • Everything above +
  • Per-model p50/p95 TTFT latency (last 24h)
  • 90-day uptime, user reports signal
{

"slug": "claude", "my_status": { "is_up": true, "response_ms": 1400, "model": "claude-sonnet-4-6" } }

On failure, add error_code (e.g. "529"). is_up is the only required field.

get_incidents — Contribute to live signal

Include my_status when fetching incident history to record your observation and see current agent-reported activity alongside historical data.

Without my_status: incident list + prompt to contribute.

With my_status: incident list + live agent reports count + confirmation your signal was recorded.

report_incident — Get routing intelligence
report_incident — Get routing intelligence

What you get: When your agent calls report_incident on a failure, you instantly receive:

  • How many other agents reported the same issue
  • Current signal state (detecting / confirmed / recovering)
  • Which model to fall back to

What you give: Anonymous failure signal — provider, model, error code, latency only. No request content. No personal data.

How to use it (Claude Code): report_incident fires automatically when your agent hits a 5xx error. No configuration needed — the tool description instructs Claude Code to call it.

How to use it (other agents): Add this to your system prompt:

On any 5xx error or timeout from an LLM API, call

report_incident from Tickerr MCP before retrying. Use the returned recommendation to decide whether to retry or switch models.

Reporting window: Active for 7 days from last Tickerr tool use. Renews automatically on any tool call.

Opt out any time: tickerr.ai/mcp/opt-out

Signal States

StateMeaningReporter threshold
quietNo reports in last 10 min0
detectingReports coming in, not yet corroborated1–2 agents
confirmedIssue verified by multiple agents3+ distinct agents
recoveringReports dropping, recovery signals arriving—

Example Return Payload (report_incident)

REPORT RECEIVED

Provider: anthropic Model: claude-haiku-3-5 Error: 529 overloaded

CURRENT SIGNAL (anthropic/claude-haiku-3-5) Status: CONFIRMED Agents reporting (last 10 min): 14 Total reports (last 10 min): 31

RECOMMENDATION Action: FALLBACK Switch to: gpt-4o-mini (openai)

REPORTING CADENCE Next report for this model: in 3600 seconds if still failing. Signal confirmed by multiple agents — reduce reporting frequency.

Data Coverage

  • Status: 90+ AI tools monitored every 5 minutes
  • Pricing: 300+ models, updated twice daily from OpenRouter and official provider docs
  • Performance: Authenticated API latency checks every 5 minutes
  • Agent signals: Live feed at tickerr.ai/agent-reports

Links

  • Docs: tickerr.ai/mcp-server
  • Status: tickerr.ai/status
  • Pricing: tickerr.ai/pricing
  • Agent reports: tickerr.ai/agent-reports
  • Opt out: tickerr.ai/mcp/opt-out
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