DataRobot

Request calculation of SHAP Preview insights with an optional data slice. Returns immediately with a queue ID - the SHAP computation happens asynchronously. Use the queue ID to poll for job status and retrieve results when complete.

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Tool to create a new modeling featurelist in a DataRobot project. Use when you need to define a custom set of features for model training.

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Tool to create a model package from a DataRobot Leaderboard model. Use after a model is trained and you need an offline package.

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Tool to create a DataRobot model package from JSON metadata. Use when you have custom model metadata and want to register it as a model package without a Leaderboard model.

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Tool to create a new notebook in DataRobot Workbench for interactive code development. Use when you need to create a Jupyter notebook for data exploration, analysis, or model development.

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Tool to create one or more environment variables for a specific notebook. Use when you need to add environment variables like API keys, credentials, or configuration values to a notebook.

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Tool to expose a port on a DataRobot notebook execution environment. Use when you need to access a web service or application running inside a notebook (e.g., Flask/FastAPI apps, Jupyter extensions, or custom web servers). The notebook must be running to expose ports. Maximum 5 ports can be exposed per notebook.

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Tool to clone a notebook from an existing revision, creating a new notebook as a copy. Use when you need to create a new notebook based on a specific revision of an existing notebook. The operation is asynchronous and returns immediately with the new notebook ID.

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Tool to create a scheduled notebook job in DataRobot. Use when you need to run a Jupyter notebook on a schedule or programmatically. The notebook must exist in DataRobot Codespaces before creating the job. Configure cron-like schedules to automate notebook execution.

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Tool to manually trigger a notebook job run in DataRobot. Use when you need to execute a notebook on-demand with optional parameters. For Codespace notebooks, both notebookId and notebookPath are required.

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Tool to create a new revision for a DataRobot notebook. Use when you need to save a checkpoint of a notebook's current state for version control or tracking changes.

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Tool to record client activity for a running notebook session. Use when tracking notebook session heartbeats or activity. This endpoint helps DataRobot track that a notebook session is still active.

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Tool to batch create multiple cells in a DataRobot notebook. Use when you need to add multiple code or markdown cells to an existing notebook at a specific position. The cells are inserted after the specified cell ID, allowing precise control over cell placement.

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Tool to batch delete multiple cells from a DataRobot notebook. Use when you need to remove multiple cells at once by their cell IDs. The deletion is permanent and cannot be undone.

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Tool to create a new notebook in DataRobot by uploading a notebook file. Use when you need to import an existing Jupyter notebook (.ipynb) into DataRobot. The notebook is created asynchronously and returns immediately with notebook metadata.

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Tool to create a notification channel template in DataRobot. Use when you need to set up notification channels for alerts, monitoring, or integration with external services. Different channel types require different parameters (e.g., Email requires emailAddress, Webhook requires payloadUrl).

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Tool to send a 6-digit verification code to a user's email address for setting up a notification channel. Use this action before creating an email notification channel to verify the email address. The verification code sent via this endpoint should be used when creating the actual email notification channel.

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Tool to test webhook notification channel configuration by creating a test notification. Use when you need to validate webhook settings before creating a production notification channel.

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Verify the notification email channel verification code. Use when an admin needs to confirm their email address for notifications by entering a 6-digit verification code.

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Tool to create an OCR (Optical Character Recognition) job resource in DataRobot. Use when you need to extract text from images or scanned documents in a dataset. The OCR job processes the input dataset and creates an output dataset with extracted text.

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Tool to create an OpenTelemetry metric configuration for a DataRobot entity (deployment, use case, etc.). Use when you need to set up custom metric tracking for monitoring entity performance.

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Tool to get OpenTelemetry metric values for a specified entity, grouped by multiple attributes. Use when analyzing metrics segmented by attributes like HTTP method, status code, or other OpenTelemetry dimensions.

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Upload a prediction dataset from a DataSource for making predictions on a DataRobot project. Returns immediately with a status URL - the upload happens asynchronously. Use when you need to make predictions using data from an external data source connector.

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Tool to initialize prediction explanations for a DataRobot model. Prediction explanations help understand which features most influenced individual predictions. Use after a model is trained to enable prediction explanation insights for that model.

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Create a new DataRobot project from a dataset URL, existing dataset ID, or data source connector. Returns immediately with a project ID and status URL - project creation happens asynchronously. Use DATAROBOT_CHECK_PROJECT_STATUS or DATAROBOT_GET_PROJECT to verify the project is ready before starting modeling.

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Tool to clone an existing DataRobot project. Use when you need to create a copy of a project with its dataset and optionally its settings. Project cloning happens asynchronously - use DATAROBOT_CHECK_PROJECT_STATUS to verify completion.

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Tool to start Autopilot on a DataRobot project with a specific feature list. Use when you need to initiate automated model building with specified Autopilot settings. Prerequisites: The project must be in 'modeling' stage with a target already set.

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Create multiple new features by transforming existing features to a different variable type. Use when you need to convert feature types in bulk (e.g., numeric to categorical, text to numeric). The operation is asynchronous - monitor the returned Location URL for completion status.

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Tool to submit a job to create bias mitigation data quality information for a given project and feature. Use when you need to create bias mitigation feature info for fairness analysis.

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Tool to create a blender model from multiple existing models in a DataRobot project. Blenders combine predictions from multiple models using methods like averaging or stacking. Use this after training multiple models to create an ensemble that may improve prediction accuracy.

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