Retrieve all schemas for a specific Apache Superset database by ID. Use it to inspect available schemas before writing SQL or building datasets.
Get schemas for a specific database
Makes a request to the /api/v1/database/{id}/schemas/ endpoint to retrieve all schemas available in the database.
Args: database_id: ID of the database
Returns: A dictionary with list of schema names
| Name | Required | Description | Default |
|---|---|---|---|
| database_id | Yes |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the API endpoint and return format, but lacks critical details such as authentication requirements, rate limits, error handling, or whether this is a read-only operation (though implied by 'Get'). For a tool with zero annotation coverage, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded with the core purpose, followed by API details and parameter/return explanations. Every sentence adds value without redundancy, making it efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (one parameter, no output schema, no annotations), the description covers the basics adequately. However, it lacks completeness for real-world use, such as authentication needs, error cases, or pagination details, which are important for a tool interacting with a database API.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaningful context for the single parameter 'database_id', explaining it as the 'ID of the database', which clarifies its purpose beyond the schema's basic type (integer). With 0% schema description coverage and only one parameter, this compensation is adequate, though it could benefit from examples or format details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Get') and resource ('schemas for a specific database'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'superset_database_get_tables' or 'superset_database_get_catalogs', which might retrieve related but different database metadata.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 any prerequisites, context for usage, or comparisons to sibling tools like 'superset_database_get_tables' or 'superset_database_get_catalogs', leaving the agent with no usage direction beyond the basic purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.