Tickerr

io.github.imviky-ctrlPublished by GitHub account imviky-ctrlv1.0.1Updated Oct 27, 2026

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

VerifiedStreamable HTTPWeb executableSecurity & MonitoringAI & ML

Overview

AI-generated overview

Tickerr gives an assistant live status, pricing, rate limits and latency data for 90+ AI tools and 300+ models, plus anonymous failure reporting.

What you can do
  • List monitored AI tools and check their three-state status (operational, degraded, down)
  • Look up token pricing per model and compare costs side by side for a given token count
  • Retrieve rate limits, quotas and free-tier details per tool and plan
  • Read incident history with severity, duration and affected components
  • Check model latency and throughput figures, including p50/p95 time-to-first-token
  • Report an API failure and get back live signal state plus a fallback recommendation
When to use it
Useful when an assistant routes between LLM providers and needs current pricing, rate limits or outage information before choosing a model, or wants a fallback suggestion after a 5xx error or timeout.
Requirements
Either the remote endpoint at tickerr.ai over streamable HTTP, or the npm package tickerr-mcp run locally with npx for stdio clients. No authentication, API keys or environment variables are declared.
Before you install
The status and incident tools ask the assistant to send its own call outcomes (up/down, response time, model, error code) to the service; reporting is described as anonymous and without request content, but it is still telemetry leaving the machine. Reporting stays active for 7 days after last use unless opted out. Pricing and status data come from third parties and may lag.

Installation

In SourceWeft

  1. Open Tickerr in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.

Use with an agent

Paste this prompt into Claude Code, Codex, Cursor or another agent — or into SourceWeft chat. The agent reads this server's install guide, shows you its publisher, endpoint and sign-in, and adds it to your client once you agree. Keys never go into a command.

Read https://sourceweft.com/mcp/io.github.imviky-ctrl%2Ftickerr/install.md and connect the MCP server it describes to my client. Before changing any config, show me its publisher, endpoint and sign-in method and wait for my OK. Never put an API key in a command or in a file I would commit; ask me where it should come from.

Read the install guide the agent follows

Other MCP clients

Add this to your client's mcpServers config.

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

README

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

json
{  "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
json
{  "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, callreport_incident from Tickerr MCP before retrying.Use the returned recommendation to decide whetherto 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 RECEIVEDProvider: anthropicModel: claude-haiku-3-5Error: 529 overloaded
CURRENT SIGNAL (anthropic/claude-haiku-3-5)Status: CONFIRMEDAgents reporting (last 10 min): 14Total reports (last 10 min): 31
RECOMMENDATIONAction: FALLBACKSwitch to: gpt-4o-mini (openai)
REPORTING CADENCENext 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

Source: README.md at commit 6c817ad

Tools

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Version history

1
  1. v1.0.1LatestSep 16, 2026

Score

75% of the applicable checks met

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