mcp-fabric-api

pipeline_get

Read-only

Retrieve detailed information about a specific data pipeline using workspace ID and pipeline ID to verify configuration, status, or metadata.

Instructions

Get details of a specific data pipeline

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "workspaceId": "<workspaceId>",
      "pipelineId": "<pipelineId>"
    },
    "name": "pipeline_get"
  }
}

Input Schema

Name	Required	Description	Default
`pipelineId`	Yes	The pipeline ID
`workspaceId`	Yes	The workspace ID

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.8.0Sep 6, 2026

TDQS

C2.9/5.0

Behavior2/5

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

The readOnlyHint=true and destructiveHint=false annotations already cover the safety profile, and the description does not contradict them. However, the description adds almost no behavioral context beyond 'Get details' — it does not describe what fields are returned, whether the tool can return errors, permission requirements, or how this differs from fetching a pipeline definition.

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

Conciseness5/5

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

The description is a single clear sentence with no filler. It is appropriately short for a simple read operation and front-loads the core action. Every word contributes to understanding the basic purpose.

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

Completeness2/5

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

There is no output schema, so the description should explain what 'details' means, but it does not. The ambiguity is significant because pipeline_get_definition exists as a sibling and likely returns a different kind of detail. The description is too thin for an agent to know what response to expect or when to prefer this tool over related getters.

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

Parameters3/5

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

Schema description coverage is 100%, with pipelineId and workspaceId both described simply as IDs. The description does not add additional meaning about how these IDs relate, how to obtain them, or whether pipelineId is scoped by workspaceId. With full schema coverage, the baseline of 3 is appropriate.

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

Purpose4/5

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

The description states a clear verb and resource: 'Get details of a specific data pipeline.' It is not a tautology and communicates the core operation. However, it does not distinguish itself from closely related siblings such as pipeline_get_definition or pipeline_get_run_status, and 'details' is somewhat vague about what is actually returned.

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

Usage Guidelines2/5

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

No when-to-use or when-not-to-use guidance is provided. The word 'specific' weakly implies this is for a single pipeline rather than a list, but the description never mentions alternatives like pipeline_list, pipeline_get_definition, or pipeline_get_run_status, so an agent gets no help choosing among them.

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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