Skip the install. Get this working in under 2 minutes.
Start a free trial on cloud.anythingmcp.com, add the Teamwork Projects in one click, then point your AI client (Claude, ChatGPT, Copilot or Cursor) at the generated MCP endpoint. No Docker, no git clone, zero engineering experience required.
Summary
Manage Teamwork.com (projects, tasks, milestones, time entries, comments, people) from any AI agent. 10 tools, basic-auth with API key.
Prova a chiedere
Prompt di esempio per Teamwork Projects
Clicca su un prompt per copiarlo. Incollalo in Claude, ChatGPT, Cursor, Gemini, Copilot o OpenClaw per eseguirlo contro questo connettore.
Claude è un'AI e può sbagliare. Verifica sempre le risposte.
💡 Niente installazione? Vai direttamente su cloud.anythingmcp.com. Accedi, clicca Connectors → Teamwork Projects, inserisci le credenziali, genera una MCP API key — fatto. Niente Docker, niente
git clone, niente server locale.
Teamwork Projects + Gemini
Manage Teamwork.com (projects, tasks, milestones, time entries, comments, people) from any AI agent. 10 tools, basic-auth with API key.
Prerequisiti
Le istruzioni di setup complete sono incluse nel connettore stesso (visibili nello store quando lo selezioni). Le variabili d'ambiente richieste sono:
TEAMWORK_SUBDOMAIN, TEAMWORK_API_KEY
Step 1 — Ottieni le credenziali
This connector wraps the Teamwork Projects REST API v3 (per-subdomain — yoursubdomain.teamwork.com/projects/api/v3).
Setup:
- Log into your Teamwork account → top-right avatar → Edit my details → API & Mobile → Get my API Key.
- Note your subdomain (the part before
.teamwork.com). - Set
TEAMWORK_SUBDOMAINandTEAMWORK_API_KEY.
Authentication: HTTP Basic — API key as username, literal x as password.
Per-tenant baseUrl: https://${TEAMWORK_SUBDOMAIN}.teamwork.com/projects/api/v3. Substituted at import time.
API versions: v3 is the modern REST. v1/v2 still exist for some endpoints. This adapter uses v3 where available.
…(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 —Teamwork Projectsdovrebbe 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 |
|---|---|
teamwork_list_projects | List projects |
teamwork_get_project | Get one project with summary metrics |
teamwork_create_project | Create a project |
teamwork_list_tasks | List tasks across all projects (or one) |
teamwork_get_task | Get one task with all custom fields, time logs, dependencies |
teamwork_create_task | Create a task inside a task list |
teamwork_complete_task | Mark a task complete |
teamwork_log_time | Log time on a task or project |
teamwork_list_milestones | List milestones across projects |
teamwork_list_people | List users (people) |
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?
