Salta l'installazione. Attivo in meno di 2 minuti.
Avvia una prova gratuita su cloud.anythingmcp.com, aggiungi GLPI con un clic, poi punta il tuo client AI (Claude, ChatGPT, Copilot o Cursor) all'endpoint MCP generato. Niente Docker, niente git clone, nessuna esperienza di sviluppo richiesta.
Summary
GLPI open-source ITSM and asset management: tickets, computers, monitors, software, users and entities, plus GLPI's search engine. REST API on your own instance, session-token auth with an App-Token.
Prova a chiedere
Prompt di esempio per GLPI
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 → GLPI, inserisci le credenziali, genera una MCP API key — fatto. Niente Docker, niente
git clone, niente server locale.
GLPI + Gemini
GLPI open-source ITSM and asset management: tickets, computers, monitors, software, users and entities, plus GLPI's search engine. REST API on your own instance, session-token auth with an App-Token.
Prerequisiti
Le istruzioni di setup complete sono incluse nel connettore stesso (visibili nello store quando lo selezioni). Le variabili d'ambiente richieste sono:
GLPI_URL, GLPI_APP_TOKEN, GLPI_USER_TOKEN
Step 1 — Ottieni le credenziali
GLPI needs two tokens, and both are easy to confuse.
- App-Token — identifies the application. In GLPI go to Setup → General → API, enable 'Enable Rest API' and 'Enable login with external token', add an API client, and copy its application token. Put it in
GLPI_APP_TOKEN. - User-Token — identifies the person. Open the GLPI user the agent should act as, go to the API tab of their profile, and regenerate the remote access key (personal API token). Put it in
GLPI_USER_TOKEN. - Set
GLPI_URLto the instance root (no trailing slash); the adapter appends/apirest.php.
…(continued in the in-app connector instructions)
Step 2 — Installa l'adapter
curl -fsSL https://raw.githubusercontent.com/HelpCode-ai/anythingmcp/main/docker-compose.quickstart.yml -o docker-compose.yml
printf 'JWT_SECRET=%s\nENCRYPTION_KEY=%s\n' "$(openssl rand -hex 32)" "$(openssl rand -hex 32)" > .env
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 —GLPIdovrebbe 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 |
|---|---|
glpi_get_active_entities | Read the entities the logged-in user is currently scoped to |
glpi_list_tickets | List tickets in the active entity with their status, priority, category, requester and dates |
glpi_get_ticket | Read one ticket in full, with its description, status, urgency, impact, priority, requester, assignee and SLA dates |
glpi_get_ticket_followups | Read the follow-ups (the conversation) on one ticket, in order, with author, date and whether each is private |
glpi_search | Run a GLPI search with criteria |
glpi_list_search_options | Read the searchable field map for one item type: which field number means status, requester, serial number and so on |
glpi_list_computers | List computers from the asset inventory with their name, serial number, model, operating system and assigned user |
glpi_get_computer | Read one computer in full: hardware, OS, network interfaces, contracts, location and the user it is assigned to |
glpi_list_users | List GLPI users with their login, name, e-mail, entity and active flag, to resolve who a ticket or an asset belongs to |
glpi_list_software | List software items from the inventory with their publisher, category and the number of installations, for licence questions |
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
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