A Python-powered interface to query Monday.com project data, boards, and team information directly via the official GraphQL API.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install native-monday
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install native-monday using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
The Monday.com skill enables AI agents to bridge the gap between project management data and automated workflows. By utilizing this integration within Openclaw Skills, developers can allow their agents to read and query boards, items, workspaces, and users directly from api.monday.com without requiring any third-party proxies. This provides a secure and direct path to high-fidelity task and project metadata.
Built on the GraphQL API (version 2024-04), this skill ensures that your AI coding agents have access to the latest project structures and item details. Whether you are building automated reporting tools or need to give your agent context on your current task list, this skill provides the necessary technical hooks to retrieve that data efficiently.
list-boards or get-board.To start using this integration with Openclaw Skills, follow these steps:
export MONDAY_API_TOKEN=your_personal_token_here
python3 /mnt/skills/user/monday/scripts/monday.py me
The skill interacts with the Monday.com GraphQL schema to retrieve data. The following table describes the primary data objects:
| Object | Description | Key Attributes |
|---|---|---|
| Boards | The primary project containers | Numeric ID, Name, Columns, Groups |
| Items | Individual tasks or rows | Item ID, Column Values, Parent Board |
| Workspaces | High-level organizational units | Workspace ID, Name, Privacy Status |
| Users | Account members | User ID, Name, Email, Account Role |
--limit flags to manage large boards and optimize performance.Loading
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