Connect Databox to AI agents

Connect Databox to Claude, Codex, Cursor, or other AI agents for your entire team. Metorial security, governance, observability, and gives your team a unified Magic MCP url to connect.

Deploy DataboxBook a demo

Supported Tools

Tools12Triggers1

create_dataset

Create Dataset

Creates a new dataset within a data source. Datasets are containers for row-level data. You can optionally define primary keys to control how rows are uniquely identified and updated during ingestion.

list_ingestions

List Ingestions

Lists ingestion events for a dataset with pagination. Use this to review the history of data pushes and track ingestion activity over time.

ingest_data

Ingest Data

Pushes a batch of data records into a Databox dataset. Each record is a JSON object whose keys match the dataset's columns. Supports real-time and event-based updates.

list_accounts

List Accounts

Retrieves all Databox accounts accessible to the authenticated user. Returns account IDs, names, and types. Use this to identify the correct **accountId** needed when creating data sources.

validate_key

Validate API Key

Validates the current API key and confirms it is active. Use this as a health check to verify that your Databox connection is working before performing other operations.

purge_dataset

Purge Dataset

Removes all rows of data from a dataset while keeping the dataset structure intact. Useful for clearing data before a full re-sync without needing to recreate the dataset.

delete_dataset

Delete Dataset

Permanently deletes a dataset and all its associated data. This action is irreversible. Use **Purge Dataset** instead if you want to clear the data but keep the dataset structure.

get_ingestion_status

Get Ingestion Status

Retrieves details about a specific data ingestion event, including processing metrics such as total rows, valid rows, and invalid rows. Use this to verify whether ingested data was processed successfully.

list_datasets

List Datasets

Lists all datasets within a specific data source. Use this to discover existing datasets before creating new ones or ingesting data.

list_timezones

List Timezones

Retrieves the full list of IANA timezone strings supported by Databox. Use a value from this list when creating or configuring a data source.

create_data_source

Create Data Source

Creates a new data source in Databox. A data source is a logical container for datasets, similar to an integration or connection. After creating a data source, you can create datasets within it and push data.

delete_data_source

Delete Data Source

Permanently deletes a data source and **all** of its contained datasets and data. This action is irreversible.

More integrations teams use with Databox

GitHub

Manage repositories, issues, and pull requests. Create and configure branches, star repositories, review code, and merge changes. Automate CI/CD workflows with GitHub Actions, manage workflow runs, secrets, and artifacts. Track issues with labels, milestones, and assignees. Search across code, repositories, issues, and users. Manage organizations, teams, and memberships. Create and manage projects, gists, packages, deployments, and environments. Access security alerts including code scanning, secret scanning, and Dependabot alerts. Read and write file contents in repositories. Manage webhooks, notifications, and codespaces.

Sharepoint

Manage SharePoint sites, document libraries, lists, and files. Create, read, update, and delete lists and list items with custom columns. Upload, download, move, copy, and version files in document libraries. Search across sites, files, folders, lists, and list items using Microsoft Search. Manage permissions at site, list, and item levels with granular access control. Define and manage content types and site columns. Subscribe to webhooks for list and library change notifications. Retrieve site properties and search for sites across Microsoft 365.

Salesforce

Manage CRM data including Accounts, Contacts, Leads, Opportunities, Cases, and custom objects. Create, read, update, and delete records. Query data using SOQL and search across objects using SOSL. Perform bulk data operations for large-scale imports, exports, and migrations. Execute composite requests to batch multiple operations in a single API call. Access analytics, reports, and dashboards. Manage files and attachments associated with records. Interact with Chatter feeds, posts, and groups for social collaboration. Subscribe to real-time change events via Change Data Capture and Platform Events. Manage org metadata including custom objects, fields, layouts, and workflows. Query data using GraphQL for precise data retrieval across related objects.

Airtable

Create, read, update, and delete records in Airtable bases and tables. Manage base schemas including creating tables and fields. Filter records using formulas, sort by fields, and scope queries to specific views. Upsert records to find, create, or update in a single call. Upload attachments to records, read and write record comments, list accessible bases, and receive real-time base change events through webhooks.

Bitbucket

Manage Git repositories, pull requests, and CI/CD pipelines on Bitbucket Cloud. Create, fork, and configure repositories within workspaces and projects. Create, review, approve, merge, and decline pull requests with inline code comments. Browse source code, list commits, and manage branches and tags. Track issues with the built-in issue tracker. Trigger, monitor, and manage Bitbucket Pipelines. List workspace members, configure repository default reviewers and branch restrictions, create and manage repository webhooks, and search code across repositories.

Heroku

Deploy, manage, and scale applications on Heroku's cloud platform. Create and configure apps, scale dynos, provision add-ons (databases, caching, etc.), manage configuration variables, build and release code, add custom domains and SSL certificates, manage collaborators and team permissions, configure pipelines for continuous delivery, set up log drains, and sync data with Salesforce via Heroku Connect. Subscribe to webhooks for real-time notifications on app changes, builds, releases, dyno lifecycle events, and more.

Technical notes for Databox

Push custom KPI and metric data into Databox for visualization and analysis. Create and manage data sources and datasets, ingest structured row-level data, track ingestion events, and configure timezones. Manage accounts, validate API keys, purge or delete datasets, and monitor data ingestion outcomes including rows processed and errors.

Connect Databox to production AI agents

See how Metorial gives Databox access the governance, tracing, and security controls teams need.

Book a demoDeploy Databox

Frequently asked questions

Common questions about connecting Databox to AI agents with Metorial.

  1. Can Metorial connect Databox to AI agents?
    Yes. Metorial connects AI agents to Databox through a governed integration layer, so teams can use the provider while keeping access controlled and observable.
  2. Metorial is MCP compatible and lets teams expose approved provider tools to MCP-capable agents and clients through a controlled access layer.
  3. Metorial applies policies across users, groups, providers, agents, and individual tools, then records the context around every agent interaction.
  4. Yes. Metorial records provider activity so teams can inspect tool calls, troubleshoot integrations, and give security teams the visibility they need.