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Cómo conectar Kustomer a Gemini — via MCP

Drive Kustomer (modern customer service CRM, Meta-owned) from any AI agent: conversations, messages, customers, notes, custom objects. 10 tools, Bearer auth.

HCBy HelpCode teamUpdated 2 min read Open source on GitHub

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MCP connector

Kustomer

Drive Kustomer (modern customer service CRM, Meta-owned) from any AI agent: conversations, messages, customers, notes, custom objects. 10 tools, Bearer auth.

Tools

10

Region

INTL

Category

support

Authentication

Bearer Token

Required env vars

KUSTOMER_API_KEYKUSTOMER_SUBDOMAIN
Install in one click on Cloud

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  • 7-day free trial
    No credit card required
  • GDPR & SOC 2 ready
    EU data residency, audit logs
  • Open-source on GitHub
    Source-available BSL-1.1
  • Works with ChatGPT, Claude, Gemini
    Any MCP-compatible client

No install? Use cloud.anythingmcp.com directly.

Sign in, install the Kustomer in one click, paste the credentials, mint an MCP API key — done. No Docker, no git clone, no local server to run.

Open Cloud

TL;DR

Drive Kustomer (modern customer service CRM, Meta-owned) from any AI agent: conversations, messages, customers, notes, custom objects. 10 tools, Bearer auth.

💡 ¿Sin instalación? Usa cloud.anythingmcp.com directamente. Inicia sesión, pulsa Connectors → Kustomer, pega tus credenciales, genera una MCP API key — listo. Sin Docker, sin git clone, sin servidor local.

Kustomer + Gemini

Drive Kustomer (modern customer service CRM, Meta-owned) from any AI agent: conversations, messages, customers, notes, custom objects. 10 tools, Bearer auth.

Requisitos previos

Las instrucciones de configuración completas están incluidas en el conector (visibles en el store al seleccionarlo). Las variables de entorno requeridas:

KUSTOMER_API_KEY, KUSTOMER_SUBDOMAIN

Paso 1 — Obtener credenciales

kustomer.com).

Setup:

  1. Sign in to Kustomer → top-right avatar → Settings → Security → API Keys → Add API Key.
  2. Pick role: org.permission.customer.read+write, org.permission.conversation.read+write, etc.
  3. Set KUSTOMER_API_KEY.
  4. Note your org subdomain (e.g. acme for acme.kustomerapp.com). Set KUSTOMER_SUBDOMAIN.

Authentication: Authorization: Bearer ${KUSTOMER_API_KEY}.

Subdomain-templated URL: https://${KUSTOMER_SUBDOMAIN}.api.kustomerapp.com/v1.

Customer-centric model: Kustomer's selling point is the unified customer timeline. A customer has multiple emails/phones/social handles; conversations roll up under the customer.

…(continued in the in-app connector instructions)

Paso 2 — Instalar el adapter

git clone https://github.com/HelpCode-ai/anythingmcp.git
cd anythingmcp && docker compose up -d

Paso 3 — Añadir el conector en Gemini

Gemini CLI lee servidores MCP desde ~/.gemini/settings.json (o %APPDATA%\gemini\settings.json en Windows). Añade:

{
  "mcpServers": {
    "anythingmcp": {
      "httpUrl": "https://cloud.anythingmcp.com/mcp",
      "headers": { "Authorization": "Bearer YOUR_MCP_API_KEY" }
    }
  }
}
  1. Obtén tu MCP API key desde AnythingMCP → Perfil → MCP API Keys → Nueva Key.
  2. Guarda el archivo y reinicia gemini.
  3. Ejecuta /mcp en la Gemini CLI — Kustomer debería aparecer como disponible.
  4. Vertex AI Studio: pasa https://cloud.anythingmcp.com/mcp al array tools de tu petición con el mismo header Bearer.

Herramientas disponibles

ToolWhat it does
kustomer_get_current_tracking_idReturn the org / org details — sanity check for API key validity
kustomer_search_customersSearch customers via the v1 search endpoint (Kustomer's Lucene-style query)
kustomer_get_customerFetch a customer by ID
kustomer_create_customerCreate a customer
kustomer_search_conversationsSearch conversations
kustomer_get_conversationFetch a conversation by ID
kustomer_update_conversationUpdate a conversation — change status (open/snoozed/done), assignee, queue, priority, tags
kustomer_add_note_to_conversationAdd an internal note (private — not sent to customer)
kustomer_create_outbound_messageSend a public message in a conversation (email/SMS/chat reply)
kustomer_list_usersList org users (agents)

FAQ

¿Gemini 1.5 Pro o 2.x soportan MCP? Sí — Gemini CLI ≥ 0.4 y la API de tools de Vertex AI aceptan conectores MCP httpUrl con header Bearer.

Siguientes pasos

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