tp is the ThinkPlatform CLI. Discover commands, inspect project resources, and automate platform operations with structured results.
Install the client
Install the CLI and Python SDK from the publicThinkPlatform-client package:
Installation
Supported platforms and package contents
Supported platforms and package contents
See Installation for environment setup, supported platforms, upgrades, and troubleshooting.Use a fresh Python environment. The initial binary wheel release targets CPython 3.11–3.13 on Linux x86_64 (glibc 2.28+), macOS 11+ on Apple silicon, and Windows x86_64. Intel Macs and public source distributions are outside this initial release.The client connects to an existing ThinkPlatform service. It includes CLI and SDK access to platform APIs, including Flow and Agent operations. The client does not include their execution engines.
Make your first read
1
Discover the available commands
Inspect help before choosing an operation. Help runs locally and does not require authentication.Command groups and flags are covered in the CLI reference.
2
Set up your profile and choose a project
Run the interactive setup in your terminal:Enter a profile name, review the connection defaults, and complete sign-in. The wizard lists accessible organizations and projects by name. Choose each by number, then confirm the summary to save and activate the profile. You do not need to look up IDs.With no connection settings configured, setup uses the production service and browser sign-in. For another deployment, use its administrator-approved settings. See Authentication.Check the saved destination. Setup requires an interactive terminal without JSON or query output; a person should complete it before handing work to an agent. Scripts can use the manual context commands.
3
Read a page and verify the result
List Canvas pages, choose an ID from the result, and read that page.Check that the returned page matches the selected project and intended title. Page content is in the top-level
blocks array. If the list is empty, use another project you can access; there is no need to create a page for this check.See Canvas pages for more read options.Give your agent a bounded task
Prepare the local Agent skills when your coding agent supports skill files. You can also follow the commands directly; skill installation does not change your platform access. Start with a request that makes the scope and expected result explicit:tp --json … requests machine-readable JSON, while --query selects a field from the result. Keep IDs from discovery output rather than guessing them. See output.
When you move on to changes, ask the agent to explain the target resources and intended effect first, then verify the resulting state with a read command.
Next steps
- Installation: prepare your environment and verify the client.
- Authentication: connect an account and manage profiles.
- Agent skills: inspect and install the bundled task guidance locally.
- Choose an organization and project: discover and verify the destination.
- Read and update Canvas pages: complete a small resource workflow.
- Files and Data Lake: upload and inspect workflow inputs.
- Run and monitor work: distinguish Flow runs, Agent tasks, and MLOps jobs.
- Troubleshooting: diagnose context, permission, and uncertain execution outcomes.
- Python SDK: use the public client from Python.