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agentcheck

io.github.agentwares/agentcheck · v0.1.1

Measured by MCP Station

Description written by the publisher, not verified

Synthetic checks, nightly regression replay and model-drift alerts for AI agents

Connect

claude mcp add --transport http agentcheck https://agentwares-agentcheck.vercel.app/api/mcp

{
  "mcpServers": {
    "agentcheck": {
      "url": "https://agentwares-agentcheck.vercel.app/api/mcp"
    }
  }
}

Tools as reported by the server

• agentcheck_get_status
  Current status of a public monitored target: overall state, uptime over 24h/7d/30d, last check time, last nightly scores, open incidents and the badge/status URLs. Use the owner (GitHub login) and target slug from the status page URL https://agentwares-agentcheck.vercel.app/<owner>/<slug>. No API ke
• agentcheck_get_pricing
  Machine-readable pricing for agentcheck: tiers with monthly USD price, target limits, check interval and features, plus per-run add-ons. Same data as /pricing.json. No API key needed.
• agentcheck_model_retirements
  Is this model retiring? Pass model IDs as your code or config names them (gpt-5-mini, claude-sonnet-4-5-20250929, gemini-2.5-flash, openai/o3-mini). For each, returns every announced shutdown on OpenAI's, Anthropic's and Google's own deprecation pages (OpenAI API, Claude API, Gemini API, Vertex AI):
• agentcheck_api_sunsets
  When does the API version this code pins stop working, and what happens then? Pass provider and version pairs as your code pins them (shopify 2025-10, meta v21.0, google-ads v22, hubspot v1, twilio-flex 2.16.2, twilio-notify v1, keap xml-rpc, exchange-online ews, stripe 2024-06-20). For each, return
• agentcheck_statuspage_preview
  Read a public Atlassian Statuspage page once: its name, overall status, components (id, name, status, group) and unresolved incidents, from the page's own /api/v2/summary.json. Pass any address on the page: status.example.com, https://status.example.com/history or the JSON URL. Use it before POST /a
• agentcheck_create_target write/delete
  Enroll something to monitor: an http endpoint (JSON or OpenAI-style chat), a remote MCP server (Streamable HTTP url) or an A2A agent (origin with /.well-known/agent-card.json). Pass `checks` to create checks in the same call (POST /api/v1/probe proposes three). Returns the target id, the public stat
• agentcheck_add_check
  Add a check to one of your targets. A check runs an input (http path/prompt, mcp tool call, a2a message) on a schedule and judges the answer with a golden: exact, contains, regex and json_schema cost nothing; rubric and baseline use the LLM judge (baseline = same outcome as the last known-good answe
• agentcheck_run_now
  Run every check of one of your targets immediately (outside the schedule) and return pass/fail per check with latency, judge cost and any incident opened or closed. Use it right after enrolling, or to confirm a fix. Requires an API key.
• agentcheck_record
  Record one production interaction with your agent (the prompt or messages, the final answer, the tools it called, optionally the model) as a trace on a target. Call it from your agent or from a proxy in front of it after each task; promote a good trace with agentcheck_promote_trace to replay it nigh
• agentcheck_promote_trace
  Turn an imported or recorded trace into a replayable check whose golden is the recorded outcome (tool sequence + final-answer rubric). The check runs daily and in the nightly replay (Pro). Returns the check. Requires an API key.
• agentcheck_list_incidents
  Open and recent incidents across your targets (or one target): when they opened/closed, the failing check and the cause. Requires an API key.

Repository · Website · JSON · Text for agents · Registry updated 2026-09-07