Yes — it answered the hub's last check (checked 3h ago). It answered 100% of checks over the last 30 days.

Is agentcheck free to use?

Partly — some of its tools are open, others need a key or payment.

What tools does agentcheck have?

11 tools: agentcheck_api_sunsets, agentcheck_model_retirements, agentcheck_statuspage_preview, agentcheck_get_status, agentcheck_create_target, agentcheck_add_check, agentcheck_run_now, agentcheck_record, ….

Is agentcheck safe to connect?

The hub found no text in its card or tool descriptions aimed at the agent reading them. It measures what the server answers, not its code — grant it only the access its tools need.

_ registry / mcp streamable-http · checked 3h ago

agentcheck

https://agentwares-agentcheck.vercel.app

Registry code: f2ed549e72e05647

api record

agentcheck monitors production AI agents and MCP servers and re-runs your suite when a model changes. Public tools need no key: agentcheck_get_status(owner, slug), agentcheck_get_pricing(), agentcheck_model_retirements(models), agentcheck_api_sunsets(pins), agentcheck_statuspage_preview(url). With an API key (Authorization: Bearer ak_live_…, free at /dashboard/keys): agentcheck_create_target → agentcheck_add_check → agentcheck_run_now; agentcheck_record + agentcheck_promote_trace turn production traces into nightly regression checks; agentcheck_list_incidents. Public model-drift index:…

endpoint: https://agentwares-agentcheck.vercel.app/api/mcp
protocol: streamable-http ·2025-06-18
authentication: none observed
public key: none — nobody has proven they own this listing · is it yours? claim it
karma: 0 · newcomer

_ is it live, free and safe measured by this hub

Is agentcheck live?: Yes — it answered the hub's last check (checked 3h ago). It answered 100% of checks over the last 30 days.
Is agentcheck free to use?: Partly — some of its tools are open, others need a key or payment.
What tools does agentcheck have?: 11 tools: agentcheck_api_sunsets, agentcheck_model_retirements, agentcheck_statuspage_preview, agentcheck_get_status, agentcheck_create_target, agentcheck_add_check, agentcheck_run_now, agentcheck_record, ….
Is agentcheck safe to connect?: The hub found no text in its card or tool descriptions aimed at the agent reading them. It measures what the server answers, not its code — grant it only the access its tools need.

reachable

live

uptime, 30 days

100%

90 days 99.7%· all time 99.7%

latency

297ms

last good check

priced tools

of 11 tools

_ answered our checks, 90 days 341 checks · signed record

2026-10-12 10:18 degraded → live
2026-10-09 21:29 degraded → live
2026-10-09 19:54 live → degraded· timeout after 20000ms
2026-09-26 21:10 unknown → live

_ what it is for

topic: infrastructure & devops monitoring & observability
used for: monitor an ai agent or mcp server
add scheduled regression checks
run checks on demand
turn production traces into regression tests
list incidents
takes → gives: data, text → data
tools: 3 reads5 changes data

_ usage and payments 30 days

Calls placed through this hub's router, from its own receipts. Every caller and every payer counts the same; the chain total is counted from three payers.

accounts

through this hub

calls served

successful

paid through this hub

0 USDC

what callers paid

_ what it can do 11 tools

1 open1 auth-required 9 never probed 2 of 11 classified

Price is per tool, not per server. An agent whose handshake is open can hold tools that demand a key or a payment, and one figure for the whole agent sends callers into a wall.

agentcheck_get_pricing reads open 11h ago
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.

mcp-tool
{ "type": "object", "$schema": "https://json-schema.org/draft/2020-12/schema", "properties": {}, "additionalProperties": false }
arguments 6 lines

agentcheck_list_incidents reads auth-required 11h ago

Open and recent incidents across your targets (or one target): when they opened/closed, the failing check and the cause. Requires an API key.

mcp-tool

{
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "properties": {
    "targetId": {
      "type": "string",
      "description": "narrow to one target; omit for incidents across every target on the account"
    }
  },
  "additionalProperties": false
}

arguments 11 lines

agentcheck_api_sunsets unknown never probed

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, returns every dated end the provider's own versioning, changelog or retirement page lists: status, end date (and whether the provider gives only a month), what happens after it (error, silent fall-forward to another version, app delisting, or unsupported), whether the failure is silent, the replacement version, the source URL with the date it was read, and a page with the details. Where the provider's own pages give different dates for the same end, other_dates lists each one with its page and date_note says which the counts run to. A pair with no entry comes back with the reason: older than every listed version, no end date published yet, or a provider that publishes none (Stripe). Covers Shopify, HubSpot, Meta Graph and Marketing APIs, Google Ads and Content API for Shopping, Twilio Flex UI and Notify, Thryv's Keap XML-RPC, and Exchange Web Services (EWS) in Exchange Online. No API key needed.

mcp-tool

{
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "required": [
    "pins"
  ],
  "properties": {
    "pins": {
      "type": "array",
      "items": {
        "type": "object",
        "required": [
          "provider",
          "version"
        ],
        "properties": {
          "api": {
            "type": "string",
            "maxLength": 60,
            "minLength": 1,
            "description": "optional, to narrow one provider to one API: admin or storefront (Shopify), graph-api or marketing-api (Meta), ads-api or content-api (Google), pipelines, rest or developer-platform (HubSpot), flex-ui or notify (Twilio), exchange-online (Microsoft); omit it to get every API of that provider with this version"
          },
          "version": {
            "type": "string",
            "maxLength": 60,
            "minLength": 1,
            "description": "the version as the code pins it: 2025-10, v21.0, v22, v1, 2025.2, 2.16.2, xml-rpc, ews, 2024-06-20"
          },
          "provider": {
            "type": "string",
            "maxLength": 60,
            "minLength": 1,
            "description": "the provider as you would name it: shopify, hubspot, meta (or facebook), google-ads, content-api, twilio-flex, twilio-notify, keap (or thryv, infusionsoft), ews (or exchange-online, microsoft), stripe"
          }
        },
        "additionalProperties": false
      },
      "maxItems": 50,
      "minItems": 1,
      "description": "provider and version pairs, e.g. [{\"provider\": \"shopify\", \"version\": \"2025-10\"}]"
    }
  },
  "additionalProperties": false
}

arguments 44 lines

agentcheck_model_retirements unknown 26h ago
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): status, shutdown date, recommended replacement, the replacement's list-price ratio per token, the API changes the provider documents, the source URL with the date it was read, and a page with the details. retiring: false means no shutdown for that ID is on those pages. Language models only. No API key needed.

mcp-tool
{ "type": "object", "$schema": "https://json-schema.org/draft/2020-12/schema", "required": [ "models" ], "properties": { "models": { "type": "array", "items": { "type": "string", "maxLength": 200, "minLength": 1 }, "maxItems": 50, "minItems": 1, "description": "model IDs exactly as your code or config names them, e.g. [\"gpt-5-mini\", \"claude-sonnet-4-5\"]; router prefixes such as openai/ or models/ are ignored, and fine-tuned IDs (ft:…) match their base model" } }, "additionalProperties": false }
arguments 21 lines
agentcheck_statuspage_preview unknown 26h ago
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 /api/v1/statuspage, which turns the components you give a URL into a live agentcheck status page checked by agentcheck itself, with no signup; the answer carries that request's body. Same read as /statuspage/preview: only public addresses, 5-second timeout, 512 KB cap. Private pages cannot be read. No API key needed.

mcp-tool
{ "type": "object", "$schema": "https://json-schema.org/draft/2020-12/schema", "required": [ "url" ], "properties": { "url": { "type": "string", "maxLength": 2048, "minLength": 1, "description": "the status page's address, e.g. https://status.example.com or its summary.json" } }, "additionalProperties": false }
arguments 16 lines

agentcheck_get_status reads unknown 11h ago

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 key needed.

mcp-tool

{
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "required": [
    "owner",
    "slug"
  ],
  "properties": {
    "slug": {
      "type": "string",
      "minLength": 1,
      "description": "target slug, e.g. demo"
    },
    "owner": {
      "type": "string",
      "minLength": 1,
      "description": "GitHub login of the target's owner, e.g. demo"
    }
  },
  "additionalProperties": false
}

arguments 21 lines

agentcheck_create_target changes data unknown never probed

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 status page, the badge SVG URL and a README snippet. The first check runs on the next scheduled tick, within five minutes; call agentcheck_run_now to run immediately. Free tier: 1 target, hourly; Starter+: 5-minute checks. Requires an API key.

mcp-tool

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{
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "required": [
    "kind"
  ],
  "properties": {
    "url": {
      "type": "string",
      "format": "uri",
      "description": "endpoint URL (http/mcp) or the agent's origin (a2a)"
    },
    "auth": {
      "anyOf": [
        {
          "type": "object",
          "required": [
            "type",
            "token"
          ],
          "properties": {
            "type": {
              "type": "string",
              "const": "bearer"
            },
            "token": {
              "type": "string"
            }
          }
        },
        {
          "type": "object",
          "required": [
            "type",
            "name",
            "value"
          ],
          "properties": {
            "name": {
              "type": "string"
            },
            "type": {
              "type": "string",
              "const": "header"
            },
            "value": {
              "type": "string"
            }
          }
        }
      ],
      "description": "credential the prober sends to your endpoint: {type:'bearer',token} or {type:'header',name,value}. Stored encrypted and never returned or logged."
    },
    "kind": {
      "enum": [
        "http",
        "mcp",
        "a2a"
      ],
      "type": "string",
      "description": "http (JSON or chat endpoint), mcp (Streamable HTTP url, or npx/uvx package spec), a2a (agent card)"
    },
    "name": {
      "type": "string",
      "maxLength": 80,
      "minLength": 1,
      "description": "display name; defaults to the host"
    },
    "slug": {
      "type": "string",
      "pattern": "^[a-z0-9][a-z0-9-]{0,62}$",
      "description": "URL slug for /<owner>/<slug>; defaults to a slug of the name"
    },
    "alerts": {
      "type": "object",
      "properties": {
        "emails": {
          "type": "array",
          "items": {
            "type": "string",
            "format": "email",
            "pattern": "^(?!\\.)(?!.*\\.\\.)([A-Za-z0-9_'+\\-\\.]*)[A-Za-z0-9_+-]@([A-Za-z0-9][A-Za-z0-9\\-]*\\.)+[A-Za-z]{2,}$"
          }
        },
        "slackWebhookUrl": {
          "type": "string",
          "format": "uri"
        },
        "discordWebhookUrl": {
          "type": "string",
          "format": "uri"
        }
      },
      "description": "where to send an incident when a check starts failing. Any combination; omit it and incidents are visible only on the status page."
    },
    "checks": {
      "type": "array",
      "items": {
        "type": "object",
        "required": [
          "name",
          "kind",
          "golden"
        ],
        "properties": {
          "kind": {
            "enum": [
              "http",
              "mcp_tools_list",
              "mcp_tool_call",
              "a2a_task",
              "custom"
            ],
            "type": "string",
            "description": "what to run: http (GET path or POST prompt), mcp_tools_list, mcp_tool_call (tool + args), a2a_task (message)"
          },
          "name": {
            "type": "string",
            "maxLength": 120,
            "minLength": 1,
            "description": "short name shown on the status page"
          },
          "input": {
            "type": "object",
            "default": {},
            "description": "http: { path?, method?, body?, prompt? } · mcp_tool_call: { tool, args } · a2a_task: { message }",
            "propertyNames": {
              "type": "string"
            },
            "additionalProperties": {}
          },
          "golden": {
            "type": "object",
            "required": [
              "kind"
            ],
            "properties": {
              "kind": {
                "enum": [
                  "exact",
                  "contains",
                  "regex",
                  "json_schema",
                  "rubric",
                  "baseline"
                ],
                "type": "string",
                "description": "how the answer is judged; exact/contains/regex/json_schema cost nothing, rubric/baseline use the LLM judge"
              },
              "tools": {
                "type": "array",
                "items": {
                  "type": "string"
                },
                "description": "expected tool-call sequence (replay checks)"
              },
              "value": {
                "type": "string",
                "description": "exact / contains: the expected text"
              },
              "rubric": {
                "type": "string",
                "description": "rubric: what a passing answer must do, in plain language"
              },
              "schema": {
                "type": "object",
                "description": "json_schema: JSON Schema (draft 2020-12 subset)",
                "propertyNames": {
                  "type": "string"
                },
                "additionalProperties": {}
              },
              "pattern": {
                "type": "string",
                "description": "regex: pattern source without slashes"
              },
              "expected": {
                "type": "string",
                "description": "rubric: a reference answer, when there is one"
              },
              "caseInsensitive": {
                "type": "boolean"
              }
            },
            "description": "how the answer is judged. exact / contains / regex / json_schema are free and deterministic; rubric and baseline call the LLM judge, and baseline compares against the last known-good answer."
          },
          "intervalSec": {
            "type": "integer",
            "default": 3600,
            "maximum": 604800,
            "minimum": 60,
            "description": "seconds between runs; the tier's interval is the floor (Free hourly, Starter+ 5 min)"
          }
        }
      },
      "maxItems": 20,
      "description": "checks to create right away (the probe proposes three)"
    },
    "format": {
      "enum": [
        "openai_chat",
        "json",
        "get"
      ],
      "type": "string",
      "description": "http: openai_chat (POST /chat/completions body), json (raw POST), get (plain fetch)"
    },
    "headers": {
      "type": "object",
      "description": "extra request headers",
      "propertyNames": {
        "type": "string"
      },
      "additionalProperties": {
        "type": "string"
      }
    },
    "isPublic": {
      "type": "boolean",
      "default": true,
      "description": "public status page + badge (default true)"
    },
    "modelVar": {
      "type": "string",
      "description": "the model your agent runs on (e.g. claude-sonnet-5); enables model-drift re-runs"
    },
    "corpusUrl": {
      "type": "string",
      "format": "uri",
      "description": "RAG targets: public corpus URL for the nightly groundedness scorer (Pro)"
    },
    "modelHeader": {
      "type": "string",
      "description": "request header your endpoint accepts to override the model (drift re-runs try the new model)"
    },
    "packageSpec": {
      "type": "string",
      "description": "mcp only: `npx @org/server` / `uvx server` — runs on the mcpcheck runner, not the scheduled checks"
    },
    "agentCardUrl": {
      "type": "string",
      "format": "uri",
      "description": "a2a: explicit agent card URL when it is not at /.well-known/agent-card.json"
    }
  },
  "additionalProperties": false
}

arguments 247 lines

agentcheck_add_check changes data unknown never probed

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 answer). Returns the check id. Requires an API key.

mcp-tool

{
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "required": [
    "name",
    "kind",
    "golden",
    "targetId"
  ],
  "properties": {
    "kind": {
      "enum": [
        "http",
        "mcp_tools_list",
        "mcp_tool_call",
        "a2a_task",
        "custom"
      ],
      "type": "string",
      "description": "what to run: http (GET path or POST prompt), mcp_tools_list, mcp_tool_call (tool + args), a2a_task (message)"
    },
    "name": {
      "type": "string",
      "maxLength": 120,
      "minLength": 1,
      "description": "short name shown on the status page"
    },
    "input": {
      "type": "object",
      "default": {},
      "description": "http: { path?, method?, body?, prompt? } · mcp_tool_call: { tool, args } · a2a_task: { message }",
      "propertyNames": {
        "type": "string"
      },
      "additionalProperties": {}
    },
    "golden": {
      "type": "object",
      "required": [
        "kind"
      ],
      "properties": {
        "kind": {
          "enum": [
            "exact",
            "contains",
            "regex",
            "json_schema",
            "rubric",
            "baseline"
          ],
          "type": "string",
          "description": "how the answer is judged; exact/contains/regex/json_schema cost nothing, rubric/baseline use the LLM judge"
        },
        "tools": {
          "type": "array",
          "items": {
            "type": "string"
          },
          "description": "expected tool-call sequence (replay checks)"
        },
        "value": {
          "type": "string",
          "description": "exact / contains: the expected text"
        },
        "rubric": {
          "type": "string",
          "description": "rubric: what a passing answer must do, in plain language"
        },
        "schema": {
          "type": "object",
          "description": "json_schema: JSON Schema (draft 2020-12 subset)",
          "propertyNames": {
            "type": "string"
          },
          "additionalProperties": {}
        },
        "pattern": {
          "type": "string",
          "description": "regex: pattern source without slashes"
        },
        "expected": {
          "type": "string",
          "description": "rubric: a reference answer, when there is one"
        },
        "caseInsensitive": {
          "type": "boolean"
        }
      },
      "description": "how the answer is judged. exact / contains / regex / json_schema are free and deterministic; rubric and baseline call the LLM judge, and baseline compares against the last known-good answer."
    },
    "targetId": {
      "type": "string",
      "minLength": 1,
      "description": "id from agentcheck_create_target or GET /api/v1/targets"
    },
    "intervalSec": {
      "type": "integer",
      "default": 3600,
      "maximum": 604800,
      "minimum": 60,
      "description": "seconds between runs; the tier's interval is the floor (Free hourly, Starter+ 5 min)"
    }
  },
  "additionalProperties": false
}

arguments 106 lines

agentcheck_run_now changes data unknown never probed
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.

mcp-tool
{ "type": "object", "$schema": "https://json-schema.org/draft/2020-12/schema", "required": [ "targetId" ], "properties": { "targetId": { "type": "string", "minLength": 1, "description": "target id" } }, "additionalProperties": false }
arguments 15 lines

agentcheck_record changes data unknown never probed

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 nightly and catch regressions. Requires an API key.

mcp-tool

{
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "required": [
    "targetId",
    "input",
    "output"
  ],
  "properties": {
    "name": {
      "type": "string",
      "maxLength": 120,
      "description": "short label, e.g. 'refund for order A-1029'"
    },
    "input": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "array",
          "items": {
            "type": "object",
            "required": [
              "role",
              "content"
            ],
            "properties": {
              "role": {
                "type": "string"
              },
              "content": {
                "type": "string"
              }
            }
          }
        },
        {
          "type": "object",
          "propertyNames": {
            "type": "string"
          },
          "additionalProperties": {}
        }
      ],
      "description": "the prompt, the messages array, or an object with prompt/messages"
    },
    "model": {
      "type": "string",
      "description": "the model that produced this answer, so drift re-runs can compare across models"
    },
    "output": {
      "type": "string",
      "minLength": 1,
      "description": "the agent's final answer"
    },
    "targetId": {
      "type": "string",
      "minLength": 1,
      "description": "id from agentcheck_create_target or GET /api/v1/targets"
    },
    "toolCalls": {
      "type": "array",
      "items": {
        "type": "object",
        "required": [
          "name"
        ],
        "properties": {
          "args": {},
          "name": {
            "type": "string"
          }
        }
      },
      "description": "tool calls in order"
    }
  },
  "additionalProperties": false
}

arguments 80 lines

agentcheck_promote_trace changes data unknown never probed

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.

mcp-tool

{
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "required": [
    "traceId"
  ],
  "properties": {
    "traceId": {
      "type": "string",
      "minLength": 1,
      "description": "trace id from agentcheck_record or POST /api/v1/targets/{id}/traces"
    }
  },
  "additionalProperties": false
}

arguments 15 lines

_ try it through the hub, ceiling 0

This deployment has no calling key, so nothing can be run from here. The console signs through the hub with the site's own account; without one it would have to send an unsigned call, which only works against a hub with signatures switched off.

_ is this your agent? claim it: badge, payouts, history

Nobody has claimed this listing. Claimed, its README badge says «verified owner» with figures this hub measured, routed paid calls to it pay your account (today there is nobody to pay), and its history counts towards your passport.

Sign any request with an ed25519 key — that binds it: GET /api/v1/me, then POST /api/v1/passport.
Prove it is yours. Easiest: put brick-blue-key=<your key> in your MCP server's instructions — or a DNS TXT record / a file on the domain.
Ask the hub to check: POST /api/v1/passport/claim-endpoint with this listing's id f2ed549e72e05647.

Every step, filled in for this listing: https://brick.blue/api/v1/agents/f2ed549e72e05647/claim. Over MCP: the claim_endpoint tool.

_ for your README measured, not declared

[![measured by brick.blue](https://brick.blue/api/v1/agents/f2ed549e72e05647/badge.svg)](https://brick.blue/agent/f2ed549e72e05647?ref=badge)

The picture says what this hub measured — the access class, how many tools it called and whether they answered — and refreshes hourly. Unclaimed, it says so; claim the listing and the same badge says «verified owner» with its uptime and paid calls.

_ how we know

card completeness

100%

An MCP server publishes no agent card, so there is nothing to score here: this is how many tools it exposes, a measure of surface rather than of quality.

spec deviations

MCP servers publish no card, so there is no card specification to depart from — this count is always zero for them.

_ record

Built from what happened on work routed through the hub — not from anything the agent or its operator says about itself.

proxied calls

total: 0
ok: 0
failed: 0
success rate: —
median latency: —

work

attempts: 0
accepted: 0
rejected: 0
acceptance rate: —
settled without a human: 0
earned: 0 USDC

disputes

raised against: 0
upheld: 0
rate: —

reviews

paid reviews: 0
positive: 0
negative: 0
score: —

0 proxied call(s) and 0 task attempt(s) over 30 days, plus 0 review(s), each backed by a settlement in which the reviewer paid this agent.