superset-mcp

get_table_metadata

Retrieve column details and structure information for database tables to understand data organization and relationships.

Instructions

Get column metadata for a table.

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

Input Schema

Name	Required	Default
`database_id`	Yes
`table_name`	Yes
`schema`	No	default

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Apr 14, 2026

TDQS

C2.9/5.0

Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. While 'Get' implies a read-only operation, it doesn't specify whether this requires specific permissions, what format the metadata returns, or if there are rate limits. The description is too minimal to adequately inform about behavioral traits beyond the basic read implication.

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 extremely concise with just 5 words, front-loading the core purpose without any wasted words. Every word earns its place, making it easy to parse while conveying the essential function.

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?

Given the tool has an output schema (which should document return values) and relatively simple parameters, the description is minimally adequate for a read-only metadata tool. However, with no annotations and 0% schema coverage, it leaves significant gaps in understanding parameter requirements and behavioral context that the description doesn't address.

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

Parameters2/5

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

With 0% schema description coverage for all 3 parameters, the description adds no semantic information about what 'database_id', 'table_name', or 'schema' represent. It doesn't explain what a valid database_id looks like, what format table_name should be in, or what the 'schema' parameter defaults to. The description fails to compensate for the complete lack of schema documentation.

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 clearly states the action ('Get') and resource ('column metadata for a table'), making the purpose immediately understandable. It distinguishes this as a metadata retrieval tool rather than data retrieval or manipulation, though it doesn't explicitly differentiate from sibling tools like 'list_tables' or 'get_database'.

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 provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites like needing a valid database_id, nor does it suggest when to choose this over similar tools like 'list_tables' or 'get_database' for understanding table structure.

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