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MarioDeFelipe

SAP Datasphere MCP Server

run_task_chain

Execute an ETL pipeline, data refresh, or synchronization job in a specified space. Returns a log ID to track asynchronous execution status.

Instructions

Execute a task chain in SAP Datasphere and get a log ID for tracking.

Use this tool when:

  • User asks to "Run the ETL pipeline" or "Execute task chain X"

  • Triggering scheduled data loads or transformations

  • Starting data replication or synchronization jobs

  • Automating data refresh workflows

  • Executing orchestrated data pipelines

What happens:

  • Task chain execution is initiated immediately

  • Returns a logId to track the execution status

  • Task runs asynchronously (use get_task_log to check status)

  • All child tasks in the chain are executed in order

Required parameters:

  • space_id: The space containing the task chain (e.g., 'SALES_SPACE')

  • object_id: The task chain name/ID (e.g., 'Daily_ETL_Pipeline')

What you'll get:

  • logId: Unique identifier to track this execution

  • Use get_task_log(space_id, logId) to monitor progress

  • Use get_task_history(space_id, object_id) to see all runs

Example queries:

  • "Run the Daily_ETL_Pipeline in SALES_SPACE"

  • "Execute task chain Customer_Sync in FINANCE_SPACE"

  • "Trigger the data refresh pipeline in ANALYTICS"

  • "Start the nightly batch job in DWH_SPACE"

Important notes:

  • Task chains run asynchronously - tool returns immediately

  • Check status with get_task_log using the returned logId

  • Requires appropriate permissions to run task chains

  • Failed runs can be investigated with detailed logs

Workflow example:

  1. Run task chain: run_task_chain(space_id='SALES', object_id='Daily_ETL')

  2. Get logId from response (e.g., 2295172)

  3. Check status: get_task_log(space_id='SALES', log_id=2295172)

  4. View details: get_task_log(space_id='SALES', log_id=2295172, detail_level='detailed')

Note: Uses API: POST /api/v1/datasphere/tasks/chains/{space_id}/run/{object_id}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
space_idYesThe space ID containing the task chain (e.g., 'SALES_SPACE', 'FINANCE'). Must be uppercase.
object_idYesThe task chain name/identifier to execute (e.g., 'Daily_ETL_Pipeline', 'Customer_Sync').
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, but description covers async execution, immediate return, required permissions, and how to track status. Includes a workflow example and notes on detailed logs.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured with sections and bullet points. Information is front-loaded with purpose. Slightly verbose but every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema, but description explains return value (logId) and how to use it. Covers workflow, example, and API endpoint. Complete for the tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and schema describes parameters. Description adds example values and notes about uppercase for space_id, but does not add significant new semantics beyond schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states it executes a task chain and returns a logId for tracking. Differentiates from sibling tools like get_task_log and get_task_history by explaining async behavior and how to use the logId.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly lists when to use (e.g., run ETL pipeline, trigger data loads) and implicitly when not to (e.g., for status checking use get_task_log). Provides workflow example and example queries.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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