mcp-fabric-api

dataflow_update

Update a Dataflow Gen2 item's display name or description in a Fabric workspace. Provide the workspace and dataflow IDs to modify its metadata.

Instructions

Update a Dataflow Gen2 item's name or description

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>",
      "dataflowId": "<dataflowId>"
    },
    "name": "dataflow_update"
  }
}

Input Schema

Name	Required	Description
`dataflowId`	Yes	The dataflow ID
`description`	No	New description
`displayName`	No	New display name
`workspaceId`	Yes	The workspace ID

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.8.0Sep 6, 2026

TDQS

A3.6/5.0

Behavior3/5

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

Annotations already indicate this is a non-read-only, non-destructive mutation. The description confirms the mutation scope (name or description) but adds no deeper behavioral context such as partial-update semantics, permission needs, or whether an update with neither field supplied is a no-op. No contradiction with annotations.

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 front-loaded sentence with no filler. It efficiently communicates the action, target resource, and affected fields.

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

Completeness4/5

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

For a simple metadata-update tool with full schema coverage and annotations covering the safety profile, the description is largely sufficient. It omits minor details like return behavior and the expectation of at least one optional field, but an agent can likely make a correct call with the available information.

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 all four parameters. The description only echoes 'name or description' and does not add meaning beyond the schema, such as clarifying that at least one optional field should be provided for a meaningful update.

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?

The description states a specific verb ('Update'), a specific resource ('Dataflow Gen2 item'), and the exact scope ('name or description'). This clearly distinguishes the tool from siblings like dataflow_create, dataflow_delete, dataflow_refresh, and dataflow_get.

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?

The description gives no explicit when-to-use guidance, no alternatives, and no prerequisites or exclusions. The intended usage must be inferred from the verb and resource, but no additional context helps an agent decide between this and related dataflow tools.

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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