Skip to main content
Glama
Sign In
Rockfish MCP Server

Rockfish MCP Server

Official
by Rockfish-Data
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

create_dataset

Creates a new dataset in Rockfish by specifying a name and optional description, so you can organize and manage data for synthetic generation or ML workflows.

Instructions

Create a new dataset

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": {
      "name": "<name>"
    },
    "name": "create_dataset"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameYesDataset name
descriptionNoDataset description

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.5/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. It signals a write/create operation but says nothing about required permissions, whether creation is idempotent, what happens on duplicate names, or what the call returns. For a mutation tool with zero annotation coverage this is a substantial gap.

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

Conciseness3/5

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

It is a single short, front-loaded sentence with no wasted words, but its brevity reflects under-specification rather than tight writing. There is no structure to speak of because there is only one clause.

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?

For a mutation tool with no annotations, no output schema, and no parameter guidance in the description, an agent is left guessing about side effects, error behavior, and return values. The description is not complete enough to support confident invocation.

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% and both parameters (name, description) are documented in the schema itself, so the baseline is 3. The description adds no extra meaning, such as name uniqueness constraints or length limits, beyond what the schema already states.

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

Purpose3/5

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

The description states a specific verb (Create) and resource (dataset), so the operation is unambiguous. However, it is essentially the tool name expanded into a sentence and adds nothing that would distinguish it from sibling creators such as create_database, create_project, or create_workflow.

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?

There is no guidance on when to use this tool versus alternatives, no mention of prerequisites (e.g., an active project context required by get_active_project), and no note about what to do if a dataset with the same name already exists.

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

Deploy Server

Other Tools