AGL Agency Capacity

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

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Qualität und Sicherheit

A
Qualität der Beschreibung
96%
Vollständigkeit des Schemas
93%
Qualität der Benennung
83%
Risiko der Vergiftung
100%
Übereinstimmung der Berechtigungen
100%
Einhaltung des Protokolls
100%

Befunde (1)

  • LOWTool 'rebrief_tax' description lacks action verbin rebrief_tax

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

Kontextkosten

~1,556Tokens (Tool-Definitionen)
~1.6 KBTypische Antwortgröße
Mittlere Auswirkung auf die Aufmerksamkeit (1.22% 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": {
    "agency-capacity": {
      "url": "https://connect.agilegrowthlabs.com/capacity"
    }
  }
}

Remote-Endpunkte

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

Was es kann

Tool-Inventar

Tools (7)

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🟢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.

Eingabe-Schema

{
  "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.

Eingabe-Schema

{
  "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.

Eingabe-Schema

{
  "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.

Eingabe-Schema

{
  "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.

Eingabe-Schema

{
  "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.

Eingabe-Schema

{
  "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.

Eingabe-Schema

{
  "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
}

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