mcp-fabric-api

pipeline_delete

Destructive

Delete a specified data pipeline in Microsoft Fabric using workspace and pipeline IDs to remove unused or erroneous pipelines from your environment.

Instructions

Delete a 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_delete"
  }
}

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?

Annotations already declare destructiveHint=true, and the description merely restates the destructive action without adding context such as irreversibility, effects on associated schedules or runs, or required permissions. It adds no behavioral information beyond the annotation.

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?

The description is a single concise sentence with no filler, but it is extremely terse and provides no contextual structure. It earns high marks for brevity but not top marks for completeness of structure.

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

Completeness3/5

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

For a simple two-parameter destructive delete with no output schema, the annotation and schema cover the core mechanics. However, the description misses side effects and alternatives, leaving the agent to infer when this operation is appropriate.

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%, so the schema already documents workspaceId and pipelineId. The description adds no parameter-level meaning, leaving it at the baseline score for fully covered schemas.

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 uses a specific verb ('Delete') and resource ('data pipeline'), making the tool's primary purpose unambiguous. It does not explicitly differentiate from closely related siblings such as pipeline_delete_schedule or deployment_pipeline_delete, so it misses the top score.

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 guidance is provided about when this tool should be used, prerequisites, or which alternatives should be chosen instead. The agent must infer usage entirely from the name and schema.

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

Deploy Server