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Superset MCP Integration

Superset MCP Integration

by aptro
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

superset_dataset_create

Create datasets in Apache Superset from existing database tables or views to enable data visualization and analysis.

Instructions

Create a new dataset in Superset

Makes a request to the /api/v1/dataset/ POST endpoint to create a new dataset from an existing database table or view.

Args: table_name: Name of the physical table in the database database_id: ID of the database where the table exists schema: Optional database schema name where the table is located owners: Optional list of user IDs who should own this dataset

Returns: A dictionary with the created dataset information including its ID

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": {
      "table_name": "<table_name>",
      "database_id": "<database_id>"
    },
    "name": "superset_dataset_create"
  }
}

Input Schema

NameRequiredDescriptionDefault
table_nameYes
database_idYes
schemaNo
ownersNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses this is a POST endpoint call (implying a write operation) and mentions the return format. However, it doesn't cover important behavioral aspects like required permissions, error conditions, rate limits, or whether this operation is idempotent.

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 well-structured with a clear purpose statement, implementation detail, parameter explanations, and return value description. It's appropriately sized for a 4-parameter creation tool, though the API endpoint detail could be considered slightly verbose.

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 creation tool with no annotations and no output schema, the description provides adequate basics but lacks important context. It explains parameters and return format but doesn't cover authentication requirements, error handling, or how this tool relates to the broader Superset dataset management workflow.

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?

With 0% schema description coverage, the description provides meaningful context for all 4 parameters. It explains what each parameter represents (table name, database ID, schema name, user IDs for ownership) and indicates which are optional vs required, adding significant value beyond the bare 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?

The description clearly states the specific action ('Create a new dataset'), the resource ('in Superset'), and the source ('from an existing database table or view'). It distinguishes this tool from sibling dataset tools like superset_dataset_get_by_id and superset_dataset_list by focusing on creation rather than retrieval.

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

Usage Guidelines3/5

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

The description implies usage when needing to create a dataset from an existing table/view, but doesn't explicitly state when to use this vs alternatives like superset_chart_create or prerequisites. No explicit exclusions or comparisons to other dataset-related tools are provided.

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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