About Agency Capacity
Capacity benchmarks, capacity math and Portable Delivery Intelligence for marketing agencies.
Configuration
Remote servers need no local install. Pick your client, then copy the config or install in one click.
https://connect.agilegrowthlabs.com/capacityclaude mcp add --transport http com-agilegrowthlabs-agency-capacity https://connect.agilegrowthlabs.com/capacity{"mcpServers":{"com-agilegrowthlabs-agency-capacity":{"type":"http","url":"https://connect.agilegrowthlabs.com/capacity"}}}Open in Cursor{"servers":{"com-agilegrowthlabs-agency-capacity":{"type":"http","url":"https://connect.agilegrowthlabs.com/capacity"}}}Open in VS Code{"mcpServers":{"com-agilegrowthlabs-agency-capacity":{"type":"http","url":"https://connect.agilegrowthlabs.com/capacity"}}}{"mcpServers":{"com-agilegrowthlabs-agency-capacity":{"serverUrl":"https://connect.agilegrowthlabs.com/capacity"}}}Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.
Tools
7| Parameter | Type | Required | Description |
|---|---|---|---|
| active_clients | integer | Yes | Active client accounts. |
| account_managers | integer | Yes | People who own client accounts day to day. |
| gross_margin_pct | number | No | Gross margin percent. Optional. |
| loaded_hourly_cost | number | No | Loaded hourly cost of an account manager in USD. Optional. |
| avg_monthly_retainer | number | No | Average monthly retainer per client in USD. Optional. |
| target_accounts_per_am | number | No | Target accounts per account manager. Default 18. |
| hours_lost_per_am_per_week | number | No | Hours each account manager loses per week to re-briefing AI, chasing approvals, fixing work and reporting. Optional. |
Details
The maintainer has not added details yet. Check the README in the repository.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.