Once the Nexadata MCP server is connected to your AI client, you can manage your Nexadata resources through conversation. This article describes the tools the server provides, grouped by function. If you have not connected the server yet, start with the companion article on setup and authentication.
Connecting and Selecting an Organization
These tools establish which organization you are working in.
list_orgs lists every organization you are a member of. The currently preferred organization is marked, and a single-org user has that organization selected automatically.
select_org sets your preferred organization for subsequent requests and confirms the organization name, ID, and slug.
Exploring Workspaces, Connections, and Datasets
Use these tools to discover what already exists in your organization.
list_workspaces lists all workspaces in an organization, including each workspace's environments and lifecycle status.
list_connections lists data connections, with optional filters for name and connection type such as
sftpors3. Results are limited to 20.search_datasets searches for datasets in an organization, with optional name and source type filters. Results are ordered by most recently updated and limited to 50.
preview_dataset downloads and displays the first 10 rows of a dataset, along with metadata and total row count.
Finding and Building Workflows
These tools let you locate workflows and assemble new ones.
list_workflows lists workflows within a specific workspace, with an optional name filter. Results are limited to 50.
workflow_lookup finds workflows by name across an organization and lists each workflow's pipelines, grouped into output pipelines and supporting pipelines. The primary output pipeline is tagged.
create_workflow creates a new workflow in a workspace and environment.
add_dataset_to_workflow associates a dataset with a workflow.
create_output_pipeline creates an output pipeline within a workflow. It takes either a dataset or a supporting pipeline as its input.
create_supporting_pipeline creates a supporting pipeline within a workflow. Supporting pipelines process data from a dataset or another supporting pipeline, and their output can feed output pipelines.
Note: When creating a pipeline, you must supply exactly one input source, either a dataset or a supporting pipeline.
Running and Monitoring Workflows
These tools trigger workflow runs and track their progress.
execute_workflow triggers a manual, background execution of a workflow. The run processes asynchronously, so the request returns execution details rather than waiting for completion.
workflow_execution_lookup looks up the status and details of a single execution, including state, timing, and any errors or warnings.
all_workflow_executions lists recent executions for a workflow, with optional filters for status, start date, and result limit.
Note: A workflow must have a default output pipeline configured before it can be executed.
Reviewing Run Statistics
These tools surface the full statistics captured during execution.
fetch_workflow_run_statistics returns execution statistics for a workflow's runs, including timing, status, and the complete statistics for each execution.
fetch_pipeline_run_statistics returns the same level of detail for an individual pipeline's executions.
Note: Both tools support filtering by status and start date, and sorting by execution.
Auditing Changes
These tools show who changed what and when.
get_pipeline_edit_attribution returns the last editor and edit timestamp for a pipeline, plus recent version snapshots with their associated execution IDs.
mapping_group_lookup finds mapping groups by name within an organization.
get_mapping_group_edit_attribution returns edit history for a mapping group, showing property changes, added, changed, and deleted mapping rules, and column changes across recent versions.
Managing Workspace Variables
These tools manage the variables scoped to a workspace.
list_variables lists all variables in a workspace with their ID, name, type, and value.
update_variable updates the value of a workspace variable.
delete_variable removes a workspace variable.
Note: Authorization for variable tools is validated through the variable, workspace, and organization chain, so you can only modify variables in organizations you belong to.