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alexander-zuev

Supabase MCP Server

get_schemas

Retrieve and list all database schemas, including their sizes and table counts, for Supabase PostgreSQL databases using the MCP protocol. Simplify database management with organized schema insights.

Instructions

List all database schemas with their sizes and table counts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • MCP tool handler registration and entrypoint for 'get_schemas'. Delegates to feature_manager.execute_tool.
    @mcp.tool(description=tool_manager.get_description(ToolName.GET_SCHEMAS))  # type: ignore
    async def get_schemas() -> QueryResult:
        """List all database schemas with their sizes and table counts."""
        return await feature_manager.execute_tool(ToolName.GET_SCHEMAS, services_container=services_container)
  • Core execution logic for get_schemas: retrieves the SQL query from query_manager and executes it using handle_query.
    async def get_schemas(self, container: "ServicesContainer") -> QueryResult:
        """List all database schemas with their sizes and table counts."""
        query_manager = container.query_manager
        query = query_manager.get_schemas_query()
        return await query_manager.handle_query(query)
  • Helper method that provides the SQL query string for listing schemas by calling SQLLoader.get_schemas_query().
    def get_schemas_query(self) -> str:
        """Get a query to list all schemas."""
        return self.sql_loader.get_schemas_query()
  • Loads the predefined SQL query for get_schemas from the file 'queries/get_schemas.sql'.
    def get_schemas_query(cls) -> str:
        """Get a query to list all schemas."""
        return cls.load_sql("get_schemas")
  • ToolName enum definition registering 'get_schemas' as a known tool.
    GET_SCHEMAS = "get_schemas"
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states this is a read operation ('List'), implying it's non-destructive, but doesn't cover other important aspects like authentication requirements, rate limits, error handling, or what the output format looks like. 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.

Conciseness5/5

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

The description is a single, efficient sentence that states exactly what the tool does with zero wasted words. It's front-loaded with the core purpose and includes key details (sizes and table counts) without unnecessary elaboration.

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's simplicity (0 parameters, no output schema, no annotations), the description is adequate but has clear gaps. It explains what the tool returns (schemas with sizes and table counts), but without annotations or output schema, it doesn't specify the return format, data types, or any behavioral constraints. This is a minimal viable description.

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?

The tool has 0 parameters, and the schema description coverage is 100% (though empty). The description doesn't need to add parameter semantics, so it meets the baseline of 4 for tools with no parameters. It appropriately doesn't mention any parameters.

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 tool's purpose with a specific verb ('List') and resource ('database schemas'), along with what information is included ('sizes and table counts'). It distinguishes from siblings like 'get_tables' and 'get_table_schema' by focusing on schemas rather than tables. However, it doesn't explicitly differentiate from all siblings, so it's not a perfect 5.

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 when to choose this over 'get_tables' or 'get_table_schema', nor does it specify any prerequisites or exclusions. The agent must infer usage from the purpose alone.

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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