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Summary
Drive Height (modern AI-native project management) from any AI agent: tasks, lists, fields, users, activities. 9 tools, API-key Bearer auth.
Try asking
Example prompts for Height
Click any prompt to copy it. Paste into Claude, ChatGPT, Cursor, Gemini, Copilot or OpenClaw to run it against this connector.
Claude is AI and can make mistakes. Please double-check responses.
💡 No install? Use cloud.anythingmcp.com directly. Sign in, click Connectors → Height, paste your credentials, mint an MCP API key — done. No Docker, no
git clone, no local server.
Height + Gemini
Drive Height (modern AI-native project management) from any AI agent: tasks, lists, fields, users, activities. 9 tools, API-key Bearer auth.
Prerequisites
See the full setup instructions baked into the connector (visible in the in-app store when you select the connector). The required environment variables for this connector are:
HEIGHT_API_KEY
Step 1 — Get credentials
Setup:
- Sign in to Height → top-right avatar → Settings → API & webhooks → Generate API key.
- Set
HEIGHT_API_KEY.
Authentication: Authorization: api-key ${HEIGHT_API_KEY} (literal api-key prefix, NOT Bearer).
Tasks are the primary object. Each task has status, name, description, assignees, dueDate, listIds[], fields (custom), parentTaskId (for subtasks).
Lists: how tasks are organized (similar to ClickUp lists or Linear projects). A task can belong to multiple lists.
Custom fields: defined at the workspace level. Reference via fields object {fieldId: value}.
Pagination: cursor-based via ?cursor=....
…(continued in the in-app connector instructions)
Step 2 — Install the adapter
curl -fsSL https://raw.githubusercontent.com/HelpCode-ai/anythingmcp/main/docker-compose.quickstart.yml -o docker-compose.yml
printf 'JWT_SECRET=%s\nENCRYPTION_KEY=%s\n' "$(openssl rand -hex 32)" "$(openssl rand -hex 32)" > .env
docker compose up -d
Step 3 — Add the connector in Gemini
Your server URL: in AnythingMCP, open MCP Servers → the server this connector is on, and copy its URL (
https://cloud.anythingmcp.com/mcp/…). Use it wherever this guide showsYOUR_SERVER_ID.
Gemini CLI reads MCP servers from ~/.gemini/settings.json (or %APPDATA%\gemini\settings.json on Windows). Add:
{
"mcpServers": {
"anythingmcp": {
"httpUrl": "https://cloud.anythingmcp.com/mcp/YOUR_SERVER_ID",
"headers": { "X-API-Key": "YOUR_MCP_API_KEY" }
}
}
}
- Get your MCP API key from AnythingMCP → MCP Servers → your server → API keys.
- Save the file and restart
gemini. - Run
/mcpinside the Gemini CLI —Heightshould be listed as available. - Vertex AI Studio: pass
https://cloud.anythingmcp.com/mcp/YOUR_SERVER_IDto thetoolsarray of your request with the sameX-API-Keyheader.
Available tools
| Tool | What it does |
|---|---|
height_get_workspace | Return workspace info: id, model, url, name |
height_list_lists | List all lists in the workspace |
height_list_tasks | List tasks with a filter query |
height_search_tasks | Full-text search tasks |
height_get_task | Fetch a single task by ID OR index (e |
height_create_task | Create a task |
height_update_task | Update a task (PATCH) |
height_list_users | List workspace users (members) |
height_list_fields | List custom fields defined in the workspace |
FAQ
Does Gemini 1.5 Pro or 2.x support MCP? Yes — Gemini CLI ≥ 0.4 and Vertex AI tools API both accept MCP httpUrl connectors with custom headers.
Next steps
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