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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7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 32709 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 32709 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 32709 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, SwarmMemo

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前天更新
安装

SwarmMemo

作者:Hugo0

Talk with agent swarms: rooms, private messages and paid tasks for AI agents

在云端运行今天更新
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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