# EVO Academia — how to use (mcp.ai)

Gym management (ABC Evo / W12): members, plans, sales, receivables, check-ins, classes and prospect CRM.

## Option A — via MCP (recommended)
Remote MCP endpoint (HTTP, streamable): `https://api.mcp.ai/p_evo?ms=1785594600000`
Add it as a custom/remote MCP connector in your client (Claude, Cursor, VS Code…), then authenticate when prompted. Once connected, ask the agent to use the server's tools (e.g. `evo_activity_list`).

## Option B — via direct REST API
Base URL: `https://api.mcp.ai/api/evo`
Auth: `Authorization: Bearer sk_live_…` — create a workspace API key at https://mcp.ai/settings/api-keys
Discover endpoints: `GET https://api.mcp.ai/api/evo/_endpoints`

### Endpoints
- `POST https://api.mcp.ai/api/evo/activity/list` — Read group activities/classes (turmas).
  - body: { date?: string, id_branch?: string, account?: string }
- `POST https://api.mcp.ai/api/evo/activity/schedule` — Read group activities/classes (turmas).
  - body: { date?: string, id_branch?: string, account?: string }
- `POST https://api.mcp.ai/api/evo/activity/write` — Enroll a member in a class or change an enrollment status.
- `POST https://api.mcp.ai/api/evo/bank/accounts` — List the gym's bank accounts.
  - body: { id_branch?: string, account?: string }
- `POST https://api.mcp.ai/api/evo/configuration` — Get the gym/branch configuration (name, timezone, gateway, occupation, card flags).
  - body: { id_branch?: string, account?: string }
- `POST https://api.mcp.ai/api/evo/employees` — List gym employees/staff.
  - body: { name?: string, email?: string, take?: integer, skip?: integer, account?: string }
- `POST https://api.mcp.ai/api/evo/entries` — List gym entries (check-ins / turnstile access), optionally by member and date range.
  - body: { member_id?: string, start_date?: string, end_date?: string, take?: integer, skip?: integer, account?: string, member_ids?: string[] }
- `POST https://api.mcp.ai/api/evo/get/member/count` — Count of active members (drives the billing tier). Returns { active, total }.
  - body: { account?: string }
- `POST https://api.mcp.ai/api/evo/list/accounts` — List all EVO gyms/branches linked to this install.
  - body: { account?: string }
- `POST https://api.mcp.ai/api/evo/member/get` — Read gym members.
  - body: { member_ids?: string[], name?: string, email?: string, document?: string, status?: string, take?: integer, skip?: integer, account?: string }
- `POST https://api.mcp.ai/api/evo/member/list` — Read gym members.
  - body: { member_ids?: string[], name?: string, email?: string, document?: string, status?: string, take?: integer, skip?: integer, account?: string }
- `POST https://api.mcp.ai/api/evo/membership` — List membership plans (planos) offered by the gym.
  - body: { id_branch?: string, account?: string }
- `POST https://api.mcp.ai/api/evo/prospect` — List prospects/leads (CRM).
  - body: { name?: string, email?: string, start_date?: string, end_date?: string, take?: integer, skip?: integer, account?: string }
- `POST https://api.mcp.ai/api/evo/prospect/write` — Create or update a prospect/lead.
- `POST https://api.mcp.ai/api/evo/receivables` — List receivables (contas a receber). Filter by date/status (PROBE: confirm param names).
  - body: { start_date?: string, end_date?: string, member_id?: string, take?: integer, skip?: integer, account?: string, member_ids?: string[] }
- `POST https://api.mcp.ai/api/evo/receivables/mark/received` — Mark a receivable as received/paid. PROBE: confirm body shape with a live gym.
- `POST https://api.mcp.ai/api/evo/sales` — List sales (vendas) over a date range.
  - body: { start_date?: string, end_date?: string, take?: integer, skip?: integer, account?: string }
- `POST https://api.mcp.ai/api/evo/sales/create` — Create a sale (e.g. sell a membership/plan to a member). PROBE: confirm body shape.

## Example prompts
- "How many active members do I have, and which receivables are overdue?"
- "List today's check-ins and the classes with open spots"
- "Show this month's sales and the new prospects to follow up"

## More
- Page: https://mcp.ai/evo
- Agent spec (llms.txt): https://mcp.ai/evo/llms.txt
- Postman collection: https://mcp.ai/evo/postman.json