agentcheck
Synthetic checks, nightly regression replay and model-drift alerts for AI agents
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Calidad y seguridad
Hallazgos (2)
- HIGHTool poisoning patterns detected
- MEDIUMTool description contains URL to non-standard domainen agentcheck_get_status
Basado en el análisis automatizado de las definiciones de herramientas y el cumplimiento del protocolo.
Costo de contexto
Este es el número aproximado de tokens que se consumen cada vez que las herramientas del servidor se cargan en el contexto de un modelo. Los recuentos más altos reducen la atención disponible para otras tareas.
Instalar
Instalación con un clic
Agrega esto a tu archivo `claude_desktop_config.json`:
{
"mcpServers": {
"agentcheck": {
"url": "https://agentwares-agentcheck.vercel.app/api/mcp"
}
}
}Puntos de conexión remotos
https://agentwares-agentcheck.vercel.app/api/mcpstreamable-httpQué puede hacer
Inventario de herramientas
Herramientas (8)
🟢agentcheck_get_status(owner, slug)
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.
Esquema de entrada
{
"type": "object",
"properties": {
"owner": {
"type": "string",
"minLength": 1,
"description": "GitHub login of the target's owner, e.g. demo"
},
"slug": {
"type": "string",
"minLength": 1,
"description": "target slug, e.g. demo"
}
},
"required": [
"owner",
"slug"
],
"$schema": "https://json-schema.org/draft/2020-12/schema",
"additionalProperties": false
}🟢agentcheck_get_pricing
Machine-readable pricing for agentcheck: tiers with monthly USD price, target limits, check interval and features, plus per-run add-ons. Same data as /pricing.json. No API key needed.
Esquema de entrada
{
"type": "object",
"properties": {},
"$schema": "https://json-schema.org/draft/2020-12/schema",
"additionalProperties": false
}🟡agentcheck_create_target(name, slug, kind, url, packageSpec, ...)
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 minute tick; call agentcheck_run_now to run immediately. Free tier: 1 target, hourly; Starter+: 5-minute checks. Requires an API key.
Esquema de entrada
{
"type": "object",
"properties": {
"name": {
"description": "display name; defaults to the host",
"type": "string",
"minLength": 1,
"maxLength": 80
},
"slug": {
"description": "URL slug for /<owner>/<slug>; defaults to a slug of the name",
"type": "string",
"pattern": "^[a-z0-9][a-z0-9-]{0,62}$"
},
"kind": {
"type": "string",
"enum": [
"http",
"mcp",
"a2a"
],
"description": "http (JSON or chat endpoint), mcp (Streamable HTTP url, or npx/uvx package spec), a2a (agent card)"
},
"url": {
"description": "endpoint URL (http/mcp) or the agent's origin (a2a)",
"type": "string",
"format": "uri"
},
"packageSpec": {
"description": "mcp only: `npx @org/server` / `uvx server` — runs on the mcpcheck runner, not the minute checks",
"type": "string"
},
"agentCardUrl": {
"description": "a2a: explicit agent card URL when it is not at /.well-known/agent-card.json",
"type": "string",
"format": "uri"
},
"format": {
"description": "http: openai_chat (POST /chat/completions body), json (raw POST), get (plain fetch)",
"type": "string",
"enum": [
"openai_chat",
"json",
"get"
]
},
"headers": {
"description": "extra request headers",
"type": "object",
"propertyNames": {
"type": "string"
},
"additionalProperties": {
"type": "string"
}
},
"auth": {
"description": "credential the prober sends to your endpoint: {type:'bearer',token} or {type:'header',name,value}. Stored encrypted and never returned or logged.",
"anyOf": [
{
"type": "object",
"properties": {
"type": {
"type": "string",
"const": "bearer"
},
"token": {
"type": "string"
}
},
"required": [
"type",
"token"
]
},
{
"type": "object",
"properties": {
"type": {
"type": "string",
"const": "header"
},
"name": {
"type": "string"
},
"value": {
"type": "string"
}
},
"required": [
"type",
"name",
"value"
]
}
]
},
"modelVar": {
"description": "the model your agent runs on (e.g. claude-sonnet-5); enables model-drift re-runs",
"type": "string"
},
"modelHeader": {
"description": "request header your endpoint accepts to override the model (drift re-runs try the new model)",
"type": "string"
},
"corpusUrl": {
"description": "RAG targets: public corpus URL for the nightly groundedness scorer (Pro)",
"type": "string",
"format": "uri"
},
"alerts": {
"description": "where to send an incident when a check starts failing. Any combination; omit it and incidents are visible only on the status page.",
"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"
}
}
},
"isPublic": {
"default": true,
"description": "public status page + badge (default true)",
"type": "boolean"
},
"checks": {
"description": "checks to create right away (the probe proposes three)",
"maxItems": 20,
"type": "array",
"items": {
"type": "object",
"properties": {
"name": {
"type": "string",
"minLength": 1,
"maxLength": 120,
"description": "short name shown on the status page"
},
"kind": {
"type": "string",
"enum": [
"http",
"mcp_tools_list",
"mcp_tool_call",
"a2a_task",
"custom"
],
"description": "what to run: http (GET path or POST prompt), mcp_tools_list, mcp_tool_call (tool + args), a2a_task (message)"
},
"input": {
"default": {},
"description": "http: { path?, method?, body?, prompt? } · mcp_tool_call: { tool, args } · a2a_task: { message }",
"type": "object",
"propertyNames": {
"type": "string"
},
"additionalProperties": {}
},
"golden": {
"type": "object",
"properties": {
"kind": {
"type": "string",
"enum": [
"exact",
"contains",
"regex",
"json_schema",
"rubric",
"baseline"
],
"description": "how the answer is judged; exact/contains/regex/json_schema cost nothing, rubric/baseline use the LLM judge"
},
"value": {
"description": "exact / contains: the expected text",
"type": "string"
},
"pattern": {
"description": "regex: pattern source without slashes",
"type": "string"
},
"caseInsensitive": {
"type": "boolean"
},
"schema": {
"description": "json_schema: JSON Schema (draft 2020-12 subset)",
"type": "object",
"propertyNames": {
"type": "string"
},
"additionalProperties": {}
},
"rubric": {
"description": "rubric: what a passing answer must do, in plain language",
"type": "string"
},
"expected": {
"description": "rubric: a reference answer, when there is one",
"type": "string"
},
"tools": {
"description": "expected tool-call sequence (replay checks)",
"type": "array",
"items": {
"type": "string"
}
}
},
"required": [
"kind"
],
"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": {
"default": 3600,
"description": "seconds between runs; the tier's interval is the floor (Free hourly, Starter+ 5 min)",
"type": "integer",
"minimum": 60,
"maximum": 604800
}
},
"required": [
"name",
"kind",
"golden"
]
}
}
},
"required": [
"kind"
],
"$schema": "https://json-schema.org/draft/2020-12/schema",
"additionalProperties": false
}🟡agentcheck_add_check(name, kind, input, golden, intervalSec, ...)
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.
Esquema de entrada
{
"type": "object",
"properties": {
"name": {
"type": "string",
"minLength": 1,
"maxLength": 120,
"description": "short name shown on the status page"
},
"kind": {
"type": "string",
"enum": [
"http",
"mcp_tools_list",
"mcp_tool_call",
"a2a_task",
"custom"
],
"description": "what to run: http (GET path or POST prompt), mcp_tools_list, mcp_tool_call (tool + args), a2a_task (message)"
},
"input": {
"default": {},
"description": "http: { path?, method?, body?, prompt? } · mcp_tool_call: { tool, args } · a2a_task: { message }",
"type": "object",
"propertyNames": {
"type": "string"
},
"additionalProperties": {}
},
"golden": {
"type": "object",
"properties": {
"kind": {
"type": "string",
"enum": [
"exact",
"contains",
"regex",
"json_schema",
"rubric",
"baseline"
],
"description": "how the answer is judged; exact/contains/regex/json_schema cost nothing, rubric/baseline use the LLM judge"
},
"value": {
"description": "exact / contains: the expected text",
"type": "string"
},
"pattern": {
"description": "regex: pattern source without slashes",
"type": "string"
},
"caseInsensitive": {
"type": "boolean"
},
"schema": {
"description": "json_schema: JSON Schema (draft 2020-12 subset)",
"type": "object",
"propertyNames": {
"type": "string"
},
"additionalProperties": {}
},
"rubric": {
"description": "rubric: what a passing answer must do, in plain language",
"type": "string"
},
"expected": {
"description": "rubric: a reference answer, when there is one",
"type": "string"
},
"tools": {
"description": "expected tool-call sequence (replay checks)",
"type": "array",
"items": {
"type": "string"
}
}
},
"required": [
"kind"
],
"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": {
"default": 3600,
"description": "seconds between runs; the tier's interval is the floor (Free hourly, Starter+ 5 min)",
"type": "integer",
"minimum": 60,
"maximum": 604800
},
"targetId": {
"type": "string",
"minLength": 1,
"description": "id from agentcheck_create_target or GET /api/v1/targets"
}
},
"required": [
"name",
"kind",
"golden",
"targetId"
],
"$schema": "https://json-schema.org/draft/2020-12/schema",
"additionalProperties": false
}🟢agentcheck_run_now(targetId)
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.
Esquema de entrada
{
"type": "object",
"properties": {
"targetId": {
"type": "string",
"minLength": 1,
"description": "target id"
}
},
"required": [
"targetId"
],
"$schema": "https://json-schema.org/draft/2020-12/schema",
"additionalProperties": false
}⚪agentcheck_record(targetId, name, input, output, toolCalls, ...)
Record one production interaction with your agent (the prompt or messages, the final answer, the tools it called, optionally the model) as a trace on a target. Call it from your agent or from a proxy in front of it after each task; promote a good trace with agentcheck_promote_trace to replay it nightly and catch regressions. Requires an API key.
Esquema de entrada
{
"type": "object",
"properties": {
"targetId": {
"type": "string",
"minLength": 1,
"description": "id from agentcheck_create_target or GET /api/v1/targets"
},
"name": {
"description": "short label, e.g. 'refund for order A-1029'",
"type": "string",
"maxLength": 120
},
"input": {
"anyOf": [
{
"type": "string"
},
{
"type": "array",
"items": {
"type": "object",
"properties": {
"role": {
"type": "string"
},
"content": {
"type": "string"
}
},
"required": [
"role",
"content"
]
}
},
{
"type": "object",
"propertyNames": {
"type": "string"
},
"additionalProperties": {}
}
],
"description": "the prompt, the messages array, or an object with prompt/messages"
},
"output": {
"type": "string",
"minLength": 1,
"description": "the agent's final answer"
},
"toolCalls": {
"description": "tool calls in order",
"type": "array",
"items": {
"type": "object",
"properties": {
"name": {
"type": "string"
},
"args": {}
},
"required": [
"name"
]
}
},
"model": {
"description": "the model that produced this answer, so drift re-runs can compare across models",
"type": "string"
}
},
"required": [
"targetId",
"input",
"output"
],
"$schema": "https://json-schema.org/draft/2020-12/schema",
"additionalProperties": false
}🟢agentcheck_promote_trace(traceId)
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.
Esquema de entrada
{
"type": "object",
"properties": {
"traceId": {
"type": "string",
"minLength": 1,
"description": "trace id from agentcheck_record or POST /api/v1/targets/{id}/traces"
}
},
"required": [
"traceId"
],
"$schema": "https://json-schema.org/draft/2020-12/schema",
"additionalProperties": false
}🟢agentcheck_list_incidents(targetId)
Open and recent incidents across your targets (or one target): when they opened/closed, the failing check and the cause. Requires an API key.
Esquema de entrada
{
"type": "object",
"properties": {
"targetId": {
"description": "narrow to one target; omit for incidents across every target on the account",
"type": "string"
}
},
"$schema": "https://json-schema.org/draft/2020-12/schema",
"additionalProperties": false
}Comunidad
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