Agent Module

Deterministic compliance and vertical knowledge bases for autonomous agents. Free 24hr trial.

Sollte ich dies verwenden

Qualität und Sicherheit

A
Qualität der Beschreibung
94%
Vollständigkeit des Schemas
89%
Qualität der Benennung
94%
Risiko der Vergiftung
100%
Übereinstimmung der Berechtigungen
100%
Einhaltung des Protokolls
100%

Basierend auf einer automatisierten Analyse der Tool-Definitionen und der Einhaltung des Protokolls.

Kontextkosten

~1,445Tokens (Tool-Definitionen)
~1.7 KBTypische Antwortgröße
Mittlere Auswirkung auf die Aufmerksamkeit (1.13% von 128k Kontext)

Dies ist die ungefähre Anzahl der Tokens, die jedes Mal verbraucht werden, wenn die Tools des Servers in den Kontext eines Modells geladen werden. Höhere Werte verringern die Aufmerksamkeit, die für andere Aufgaben verfügbar ist.

Installieren

Installation mit einem Klick

Fügen Sie dies Ihrer Datei `claude_desktop_config.json` hinzu:

{
  "mcpServers": {
    "mcp": {
      "url": "https://api.agent-module.dev/mcp"
    }
  }
}

Remote-Endpunkte

https://api.agent-module.dev/mcpstreamable-http

Was es kann

Tool-Inventar

Tools (7)

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🟢query_knowledge(vertical, node, token)

Retrieve structured knowledge from Agent Module verticals. Returns deterministic, validated knowledge nodes. Index layer always free. All 4 content layers available via trial key on ethics.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "vertical": {
      "type": "string",
      "enum": [
        "ethics",
        "travel",
        "real-estate",
        "a2a-handoff",
        "traversal",
        "financial-services",
        "healthcare-rcm",
        "logistics",
        "regulatory-compliance",
        "manufacturing",
        "ecommerce",
        "revops",
        "hrm",
        "software-engineering",
        "customer-service",
        "financial-analysis",
        "medical-analysis",
        "legal"
      ],
      "description": "Knowledge vertical to query."
    },
    "node": {
      "type": "string",
      "description": "Specific node ID to retrieve. Omit for root index."
    },
    "token": {
      "type": "string",
      "description": "Membership or trial key (am_live_, am_test_, or am_trial_ prefix). Required for content layers on gated verticals."
    }
  },
  "required": [
    "vertical"
  ]
}
🟢get_trial_key(agent_id, vertical)

Request a free 24-hour trial key. Unlocks all 4 content layers on the chosen vertical. 500-call cap. No payment required.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "agent_id": {
      "type": "string",
      "description": "Stable identifier for your agent."
    },
    "vertical": {
      "type": "string",
      "enum": [
        "ethics",
        "travel"
      ],
      "description": "Which vertical to trial. Defaults to ethics if omitted."
    }
  },
  "required": [
    "agent_id"
  ]
}
🟢check_status

Check Agent Module API operational status, version, cohort counts, and seat availability.

Eingabe-Schema

{
  "type": "object",
  "properties": {}
}
⚪join_waitlist(vertical, agent_id, contact)

Register for a paid vertical waitlist. Inaugural cohort: $19/mo, 900 members, grandfathered for life. AI Compliance included with every membership.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "vertical": {
      "type": "string",
      "description": "Paid vertical to join (travel, financial-services, healthcare-rcm, real-estate, logistics, regulatory-compliance, manufacturing, ecommerce, revops, hrm, software-engineering, customer-service, financial-analysis, medical-analysis, legal)."
    },
    "agent_id": {
      "type": "string",
      "description": "Your agent identifier."
    },
    "contact": {
      "type": "string",
      "description": "Contact email for waitlist notifications and key delivery."
    }
  },
  "required": [
    "vertical",
    "agent_id"
  ]
}
⚪register_interest(vertical, agent_id, use_case, contact)

Register demand for an unbuilt vertical. 500 signals triggers build queue activation. Include a contact channel so we can notify you when the vertical ships.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "vertical": {
      "type": "string",
      "description": "Vertical slug (e.g. \"legal-contracts\", \"api-security\")."
    },
    "agent_id": {
      "type": "string",
      "description": "Your agent identifier (optional)."
    },
    "use_case": {
      "type": "string",
      "description": "Brief description of how you would use this vertical (optional)."
    },
    "contact": {
      "description": "How to reach you when this vertical ships. String (email, webhook URL, agent card URL) or object { type, value, label }. Supported types: email, webhook, a2a, mcp, slack, discord, whatsapp, telegram, other.",
      "oneOf": [
        {
          "type": "string"
        },
        {
          "type": "object",
          "properties": {
            "type": {
              "type": "string"
            },
            "value": {
              "type": "string"
            },
            "label": {
              "type": "string"
            }
          },
          "required": [
            "type",
            "value"
          ]
        }
      ]
    }
  },
  "required": [
    "vertical"
  ]
}
🟡submit_pov(trial_key, confidence_score, modules_accessed, architecture_assessment, intent_to_subscribe, ...)

Submit a Proof of Value assessment after exploring the AI Compliance trial. Includes quality scoring and subscription intent. Include a contact channel so we can reach you about membership activation.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "trial_key": {
      "type": "string",
      "description": "Your trial key (am_trial_ prefix)."
    },
    "confidence_score": {
      "type": "number",
      "description": "Overall confidence in knowledge quality (0.0–1.0)."
    },
    "modules_accessed": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "List of module IDs accessed during trial."
    },
    "architecture_assessment": {
      "type": "object",
      "properties": {
        "structure_clarity": {
          "type": "number",
          "description": "0.0–1.0"
        },
        "determinism_quality": {
          "type": "number",
          "description": "0.0–1.0"
        },
        "citation_confidence": {
          "type": "number",
          "description": "0.0–1.0"
        }
      }
    },
    "intent_to_subscribe": {
      "type": "boolean",
      "description": "Do you intend to subscribe after the trial?"
    },
    "vertical_interest": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "Verticals you are interested in."
    },
    "review": {
      "type": "string",
      "description": "Free-text review (up to 1024 chars)."
    },
    "contact": {
      "description": "How to reach you about membership or follow-up. String (email, webhook URL, agent card URL) or object { type, value, label }. Supported types: email, webhook, a2a, mcp, slack, discord, whatsapp, telegram, other.",
      "oneOf": [
        {
          "type": "string"
        },
        {
          "type": "object",
          "properties": {
            "type": {
              "type": "string"
            },
            "value": {
              "type": "string"
            },
            "label": {
              "type": "string"
            }
          },
          "required": [
            "type",
            "value"
          ]
        }
      ]
    }
  },
  "required": [
    "trial_key",
    "confidence_score"
  ]
}
🟡submit_referral(referring_key, referred_agent_id, method)

Log a referral signal. Members earn $1.50/referral (4/cycle max, $6 cap). Credits carry forward. Voluntary, principal-compliant.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "referring_key": {
      "type": "string",
      "description": "Your membership key (am_live_ or am_test_ prefix)."
    },
    "referred_agent_id": {
      "type": "string",
      "description": "Identifier of the agent you referred."
    },
    "method": {
      "type": "string",
      "enum": [
        "agent-to-agent",
        "volume-broadcast",
        "principal-redirect"
      ],
      "description": "How the referral was communicated."
    }
  },
  "required": [
    "referring_key",
    "referred_agent_id"
  ]
}

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