AGL Agency Capacity

Agency capacity math, benchmarks, client context templates and an AI approval checklist.

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Calidad y seguridad

A
Calidad de la descripción
96%
Integridad del esquema
93%
Calidad de los nombres
83%
Riesgo de envenenamiento
100%
Coincidencia de permisos
100%
Cumplimiento del protocolo
100%

Hallazgos (1)

  • LOWTool 'rebrief_tax' description lacks action verben rebrief_tax

Basado en el análisis automatizado de las definiciones de herramientas y el cumplimiento del protocolo.

Costo de contexto

~1,556Tokens (definiciones de herramientas)
~1.6 KBTamaño de respuesta típico
Impacto moderado en la atención (1.22% del contexto de 128k)

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": {
    "agency-capacity": {
      "url": "https://connect.agilegrowthlabs.com/capacity"
    }
  }
}

Puntos de conexión remotos

https://connect.agilegrowthlabs.com/capacitystreamable-http

Qué puede hacer

Inventario de herramientas

Herramientas (7)

🟢 Solo lectura🟡 Escritura🔴 Eliminación⚪ Desconocido
🟢capacity_check(active_clients, account_managers, avg_monthly_retainer, hours_lost_per_am_per_week, loaded_hourly_cost, ...)

Estimates an agency's accounts per account manager, yearly coordination cost, and how many more accounts the same team could carry at a target ratio. Use when the user shares client and team numbers and asks about capacity, hiring, or account manager load. Returns an estimate, not a guarantee.

Esquema de entrada

{
  "type": "object",
  "properties": {
    "active_clients": {
      "type": "integer",
      "minimum": 1,
      "maximum": 2000,
      "description": "Active client accounts."
    },
    "account_managers": {
      "type": "integer",
      "minimum": 1,
      "maximum": 500,
      "description": "People who own client accounts day to day."
    },
    "avg_monthly_retainer": {
      "type": "number",
      "minimum": 0,
      "maximum": 1000000,
      "description": "Average monthly retainer per client in USD. Optional."
    },
    "hours_lost_per_am_per_week": {
      "type": "number",
      "minimum": 0,
      "maximum": 60,
      "description": "Hours each account manager loses per week to re-briefing AI, chasing approvals, fixing work and reporting. Optional."
    },
    "loaded_hourly_cost": {
      "type": "number",
      "minimum": 0,
      "maximum": 1000,
      "description": "Loaded hourly cost of an account manager in USD. Optional."
    },
    "gross_margin_pct": {
      "type": "number",
      "minimum": 0,
      "maximum": 100,
      "description": "Gross margin percent. Optional."
    },
    "target_accounts_per_am": {
      "type": "number",
      "minimum": 1,
      "maximum": 40,
      "default": 18,
      "description": "Target accounts per account manager. Default 18."
    }
  },
  "required": [
    "active_clients",
    "account_managers"
  ],
  "additionalProperties": false
}
🟢rebrief_tax(minutes_per_rebrief, rebriefs_per_account_per_week, accounts_per_person, people, hourly_cost)

Estimates the monthly hours and cost a team spends explaining clients to AI tools before they do useful work. Use when the user asks what re-briefing AI or re-pasting client context costs.

Esquema de entrada

{
  "type": "object",
  "properties": {
    "minutes_per_rebrief": {
      "type": "number",
      "minimum": 0,
      "maximum": 120,
      "description": "Minutes spent loading client context into a new AI chat."
    },
    "rebriefs_per_account_per_week": {
      "type": "number",
      "minimum": 0,
      "maximum": 100,
      "description": "New AI chats per account per person each week."
    },
    "accounts_per_person": {
      "type": "number",
      "minimum": 0,
      "maximum": 100,
      "description": "Accounts each person works on."
    },
    "people": {
      "type": "integer",
      "minimum": 1,
      "maximum": 1000,
      "description": "People who use AI on client work."
    },
    "hourly_cost": {
      "type": "number",
      "minimum": 0,
      "maximum": 1000,
      "description": "Loaded hourly cost in USD. Optional."
    }
  },
  "required": [
    "minutes_per_rebrief",
    "rebriefs_per_account_per_week",
    "accounts_per_person",
    "people"
  ],
  "additionalProperties": false
}
🟢capacity_benchmarks(topic)

Returns published benchmarks on accounts per account manager, time spent re-briefing AI, and rework of AI output, each with its source link. Use when the user asks what is normal for agencies.

Esquema de entrada

{
  "type": "object",
  "properties": {
    "topic": {
      "type": "string",
      "enum": [
        "all",
        "accounts_per_person",
        "rebriefing",
        "rework"
      ],
      "default": "all",
      "description": "Which benchmarks to return."
    }
  },
  "additionalProperties": false
}
🟢client_context_template(service_line, client_name)

Returns a fill-in template for a 1-file client context document (goals, voice, claims rules, priorities, approvals, decisions) for a service line. Use when the user wants AI tools or new teammates to stop needing a client re-brief.

Esquema de entrada

{
  "type": "object",
  "properties": {
    "service_line": {
      "type": "string",
      "enum": [
        "general",
        "seo",
        "paid_media",
        "content",
        "lifecycle",
        "automation"
      ],
      "description": "general, seo, paid_media, content, lifecycle, or automation. Default general."
    },
    "client_name": {
      "type": "string",
      "maxLength": 80,
      "description": "Optional client name to put in the title."
    }
  },
  "additionalProperties": false
}
🟢approval_checklist(service_line)

Returns an 8-check review list for AI-drafted client work, plus checks for the service line and how much review each risk level needs. Use when the user asks how to QA AI output before it reaches a client.

Esquema de entrada

{
  "type": "object",
  "properties": {
    "service_line": {
      "type": "string",
      "enum": [
        "general",
        "seo",
        "paid_media",
        "content",
        "lifecycle",
        "automation"
      ],
      "description": "general, seo, paid_media, content, lifecycle, or automation. Default general."
    }
  },
  "additionalProperties": false
}
🟢define_term(term)

Defines an agency AI operations term, such as Portable Delivery Intelligence, accounts per person, re-brief tax, or AI operations sprawl. Leave term empty to list all terms.

Esquema de entrada

{
  "type": "object",
  "properties": {
    "term": {
      "type": "string",
      "maxLength": 80,
      "description": "The term to define. Optional."
    }
  },
  "additionalProperties": false
}
🟡add_to_benchmark(consent, role, revenue_band, active_clients, account_managers, ...)

Adds 1 anonymous response to the Agency Capacity Benchmark run by Agile Growth Labs. Only call when the user explicitly agrees to share their numbers. Stores no name, email, or company. Max 3 per day per network.

Esquema de entrada

{
  "type": "object",
  "properties": {
    "consent": {
      "type": "boolean",
      "description": "Must be true. The user agreed to add anonymous numbers."
    },
    "role": {
      "type": "string",
      "enum": [
        "owner-founder",
        "coo-ops",
        "delivery-account-lead",
        "other"
      ]
    },
    "revenue_band": {
      "type": "string",
      "enum": [
        "under-1m",
        "1m-2m",
        "2m-5m",
        "5m-10m",
        "10m-plus"
      ]
    },
    "active_clients": {
      "type": "integer",
      "minimum": 1,
      "maximum": 2000
    },
    "account_managers": {
      "type": "integer",
      "minimum": 1,
      "maximum": 500
    },
    "rebrief_hours_per_week": {
      "type": "number",
      "minimum": 0,
      "maximum": 80,
      "description": "Team hours per week spent re-briefing AI tools."
    },
    "ai_tools_count": {
      "type": "integer",
      "minimum": 0,
      "maximum": 50,
      "description": "AI tools used in client work."
    },
    "bottleneck": {
      "type": "string",
      "enum": [
        "rebriefing",
        "approvals",
        "fixing",
        "reporting",
        "hiring",
        "other"
      ],
      "description": "The biggest delivery bottleneck."
    }
  },
  "required": [
    "consent",
    "role",
    "revenue_band",
    "active_clients",
    "account_managers",
    "rebrief_hours_per_week",
    "ai_tools_count",
    "bottleneck"
  ],
  "additionalProperties": false
}

Comunidad

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Evidencia

Observaciones recientes

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