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Built for the Claude Code community with Claude Code by mertbuilds.com

Independent project, not affiliated with Anthropic
imviky-ctrl avatar

Tickerr

imviky-ctrl/tickerr-mcp
1STDIO, HTTPregistry active
Summary

Connects your agent to live status, pricing, and performance data for ChatGPT, Claude, Gemini, Cursor, and 40+ other AI tools. Nine tools cover token pricing for 300+ models, rate limits, free tier details, historical incidents, and per-model TTFT latency. The interesting bit is the give and take model: when your agent reports successful or failed API calls via my_status parameters, you unlock richer data like p50/p95 latency and agent-reported failure signals. Call report_incident on 5xx errors and you get back how many other agents are seeing the same issue plus a fallback recommendation. No auth required. Useful for multi-model routing, cost optimization, and real-time failure detection when you're orchestrating calls across providers.

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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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Categories
AI & LLM Tools
Registryactive
Packagetickerr-mcp
TransportSTDIO, HTTP
UpdatedApr 14, 2026
View on GitHub

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