No install? Use cloud.anythingmcp.com directly.
Sign in, install the BambooHR in one click, paste the credentials, mint an MCP API key — done. No Docker, no git clone, no local server to run.
TL;DR
Manage BambooHR (employees, time-off, custom reports, fields, files) from any AI agent. 9 tools, basic-auth.
💡 Niente installazione? Vai direttamente su cloud.anythingmcp.com. Accedi, clicca Connectors → BambooHR, inserisci le credenziali, genera una MCP API key — fatto. Niente Docker, niente
git clone, niente server locale.
BambooHR + Gemini
Manage BambooHR (employees, time-off, custom reports, fields, files) from any AI agent. 9 tools, basic-auth.
Prerequisiti
Le istruzioni di setup complete sono incluse nel connettore stesso (visibili nello store quando lo selezioni). Le variabili d'ambiente richieste sono:
BAMBOOHR_SUBDOMAIN, BAMBOOHR_API_KEY
Step 1 — Ottieni le credenziali
This connector wraps the BambooHR REST API v1 (per-subdomain — api.bamboohr.com/api/gateway.php/<subdomain>/v1).
Setup:
- Sign in to your BambooHR portal → top-right avatar → API Keys → Add a new key.
- Note your subdomain (the part before
.bamboohr.com) and copy the key. - Set
BAMBOOHR_SUBDOMAINandBAMBOOHR_API_KEY.
Authentication: HTTP Basic — API key as username, literal x as password.
Path subdomain: BambooHR's API embeds the subdomain in the URL path. The adapter substitutes via runtime envVar.
…(continued in the in-app connector instructions)
Step 2 — Installa l'adapter
git clone https://github.com/HelpCode-ai/anythingmcp.git
cd anythingmcp && docker compose up -d
Step 3 — Aggiungi il connettore in Gemini
Gemini CLI legge i server MCP da ~/.gemini/settings.json (o %APPDATA%\gemini\settings.json su Windows). Aggiungi:
{
"mcpServers": {
"anythingmcp": {
"httpUrl": "https://cloud.anythingmcp.com/mcp",
"headers": { "Authorization": "Bearer YOUR_MCP_API_KEY" }
}
}
}
- Ottieni la tua MCP API key da AnythingMCP → Profilo → MCP API Keys → Nuova Key.
- Salva il file e riavvia
gemini. - Esegui
/mcpnella Gemini CLI —BambooHRdovrebbe essere elencato come disponibile. - Vertex AI Studio: passa
https://cloud.anythingmcp.com/mcpnell'arraytoolsdella richiesta con lo stesso header Bearer.
Tool disponibili
| Tool | What it does |
|---|---|
bamboohr_list_employees_directory | Returns the company directory: every employee's id, displayName, jobTitle, workEmail, department, division, location, supervisor |
bamboohr_get_employee | Get one employee by ID |
bamboohr_add_employee | Create a new employee |
bamboohr_update_employee | Update employee fields |
bamboohr_who_is_out | Returns the company-wide who's-out list for a date range |
bamboohr_list_time_off_requests | List time-off requests |
bamboohr_list_meta_fields | List every field defined in this account (built-in + custom) |
bamboohr_run_custom_report | Run a pre-defined custom report by its numeric ID |
bamboohr_get_employee_files | List files in an employee's record categorized by section |
FAQ
Gemini 1.5 Pro o 2.x supportano MCP? Sì — Gemini CLI ≥ 0.4 e la Vertex AI tools API accettano connettori MCP httpUrl con header Bearer.
Prossimi passi
Questa guida ti è stata utile?