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Cómo conectar Height a Gemini — via MCP

Drive Height (modern AI-native project management) from any AI agent: tasks, lists, fields, users, activities. 9 tools, API-key Bearer auth.

HCBy HelpCode teamUpdated 2 min read Open source on GitHub

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MCP connector

Height

Drive Height (modern AI-native project management) from any AI agent: tasks, lists, fields, users, activities. 9 tools, API-key Bearer auth.

Tools

9

Region

INTL

Category

project-management

Authentication

API Key

Required env vars

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

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TL;DR

Drive Height (modern AI-native project management) from any AI agent: tasks, lists, fields, users, activities. 9 tools, API-key Bearer auth.

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

Height + Gemini

Drive Height (modern AI-native project management) from any AI agent: tasks, lists, fields, users, activities. 9 tools, API-key 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:

HEIGHT_API_KEY

Paso 1 — Obtener credenciales

app/api/docs).

Setup:

  1. Sign in to Height → top-right avatar → Settings → API & webhooks → Generate API key.
  2. Set HEIGHT_API_KEY.

Authentication: Authorization: api-key ${HEIGHT_API_KEY} (literal api-key prefix, NOT Bearer).

Tasks are the primary object. Each task has status, name, description, assignees, dueDate, listIds[], fields (custom), parentTaskId (for subtasks).

Lists: how tasks are organized (similar to ClickUp lists or Linear projects). A task can belong to multiple lists.

Custom fields: defined at the workspace level. Reference via fields object {fieldId: value}.

Pagination: cursor-based via ?cursor=....

…(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 — Height 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
height_get_workspaceReturn workspace info: id, model, url, name
height_list_listsList all lists in the workspace
height_list_tasksList tasks with a filter query
height_search_tasksFull-text search tasks
height_get_taskFetch a single task by ID OR index (e
height_create_taskCreate a task
height_update_taskUpdate a task (PATCH)
height_list_usersList workspace users (members)
height_list_fieldsList custom fields defined in the workspace

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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