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alaturqua

MCP Trino Server

by alaturqua

show_refs

Retrieve branches and tags for an Iceberg table by providing the catalog, schema, and table name.

Instructions

Show Iceberg table references (branches and tags)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
catalogYescatalog name
schema_nameYesschema name
tableYesThe name of the table

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • MCP tool handler for 'show_refs'. Decorated with @mcp.tool, defines the schema via Pydantic Field parameters (catalog, schema_name, table), and delegates to client.show_refs().
    @mcp.tool(description="Show Iceberg table references (branches and tags)")
    def show_refs(
        catalog: str = Field(description="catalog name "),
        schema_name: str = Field(description="schema name "),
        table: str = Field(description="The name of the table"),
    ) -> str:
        """Show Iceberg table references (branches and tags).
    
        The refs table contains:
        - name: Name of the reference
        - type: Type of reference (BRANCH or TAG)
        - snapshot_id: ID of referenced snapshot
        - max_reference_age_in_ms: Max age before reference expiry
        - min_snapshots_to_keep: Min snapshots to keep (branches only)
        - max_snapshot_age_in_ms: Max snapshot age in branch
    
        Args:
            catalog: catalog name
            schema_name: schema name
            table: The name of the table
    
        Returns:
            str: JSON-formatted table references
        """
        return client.show_refs(catalog, schema_name, table)
  • Client method show_refs() that constructs and executes the query 'SELECT * FROM "{catalog}.{schema}.{table}$refs"' on the Iceberg refs table, returning JSON-formatted results.
    def show_refs(self, table: str, catalog: str, schema: str) -> str:
        """Show Iceberg table references (branches and tags).
    
        The refs table contains:
        - name: VARCHAR - Name of the reference
        - type: VARCHAR - Type of reference (BRANCH or TAG)
        - snapshot_id: BIGINT - ID of referenced snapshot
        - max_reference_age_in_ms: BIGINT - Max age before reference expiry
        - min_snapshots_to_keep: INTEGER - Min snapshots to keep (branches only)
        - max_snapshot_age_in_ms: BIGINT - Max snapshot age in branch
    
        Args:
            table: The name of the table
            catalog: Optional catalog name (defaults to configured catalog)
            schema: Optional schema name (defaults to configured schema)
    
        Returns:
            str: JSON-formatted string containing table references
        """
        catalog = catalog or self.config.catalog
        schema = schema or self.config.schema
        if not catalog or not schema:
            raise CatalogSchemaError
        table_identifier = f"{catalog}.{schema}.{table}$refs"
        query = 'SELECT * FROM "{}"'
        return self.execute_query(query.format(table_identifier))
  • src/server.py:468-468 (registration)
    Registration via @mcp.tool decorator with description 'Show Iceberg table references (branches and tags)'.
    @mcp.tool(description="Show Iceberg table references (branches and tags)")
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 only states the purpose and does not mention safety, permissions, rate limits, or any side effects. For a read-like operation, the lack of explicit read-only indication is a gap.

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, concise sentence with no extraneous words. It effectively communicates the core purpose.

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?

The tool has an output schema, so the description need not explain return values. However, given the lack of usage examples and behavioral details, the description is adequate but minimal for a simple show tool.

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?

The input schema has 100% coverage with descriptions for all three parameters (catalog, schema_name, table). The description adds no additional meaning beyond what the schema already provides, so the baseline score of 3 is appropriate.

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 tool's purpose: 'Show Iceberg table references (branches and tags)'. It specifies a verb ('Show'), a resource ('Iceberg table references'), and clarifies what type of references (branches and tags), distinguishing it from sibling show tools like show_snapshots, show_files, etc.

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 the user needs to see branches or tags, but does not explicitly state when to use this tool versus other show tools or provide any exclusions. The context of sibling names helps differentiate, but the description itself offers no guidance.

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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