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)

| Tool | What it does | |------|-------------| | get_api_pricing | Current input/output/cached token costs for 300+ models. Updated twice daily. | | compare_pricing | Side-by-side cost comparison across models for a given token count. | | get_tool_status | Live uptime status and 90-day incident history for any AI service. | | get_incidents | Recent incidents for a tool — severity, duration, affected components. | | get_rate_limits | Per-plan rate limits and quotas for any AI tool. | | get_free_tier | Free tier details — what's included, what's limited. | | get_model_performance | p50/p95 latency and tokens/sec from authenticated API calls. | | list_tools | Full list of tools and models tracked by Tickerr. | | report_incident | Report an LLM API failure. Returns live signal from other agents and a routing recommendation. Anonymous. |

Agent Reporting — Give and Take

Tickerr MCP uses a give-and-take model for the report_incident tool.

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

| State | Meaning | Reporter threshold | |-------|---------|-------------------| | quiet | No reports in last 10 min | 0 | | detecting | Reports coming in, not yet corroborated | 1–2 agents | | confirmed | Issue verified by multiple agents | 3+ distinct agents | | recovering | Reports 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