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IcebergMCP

by ryft-io

get_iceberg_tables

Retrieve a list of Apache Iceberg tables from a specified namespace to access and manage data lakehouse metadata through the IcebergMCP server.

Instructions

Provides a list of iceberg tables from the Iceberg catalog for a given namespace

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
namespaceYes

Implementation Reference

  • The handler function for the 'get_iceberg_tables' tool, decorated with @mcp.tool() for registration. It retrieves the list of tables in the specified namespace from the Iceberg Glue catalog and returns their names as a newline-separated string.
    @mcp.tool()
    def get_iceberg_tables(namespace: str) -> str:
        """Provides a list of iceberg tables from the Iceberg catalog for a given namespace"""
        catalog = get_catalog()
        tables = catalog.list_tables(namespace)
        return "\n".join(t[1] for t in tables)
  • Helper function used by the tool to initialize and return the AWS Glue Catalog instance for accessing Iceberg tables.
    def get_catalog() -> GlueCatalog:
        try:
            session = boto3.Session(profile_name=iceberg_config.profile_name)
            credentials = session.get_credentials().get_frozen_credentials()
    
            catalog = GlueCatalog(
                "glue",
                **{
                    "client.access-key-id": credentials.access_key,
                    "client.secret-access-key": credentials.secret_key,
                    "client.session-token": credentials.token,
                    "client.region": iceberg_config.region,
                },
            )
        except Exception as e:
            logger.error(f"Error creating AWS connection: {str(e)}")
            raise
        return catalog
  • The @mcp.tool() decorator registers the get_iceberg_tables function as an MCP tool.
    @mcp.tool()

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior2/5

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

No annotations are provided, so the description carries full burden. It only states the action ('provides a list') without disclosing behavioral traits such as read-only semantics, authentication requirements, rate limits, or side effects. The description is too minimal to inform safe usage.

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 sentence with 11 words, no filler, and front-loads the core action. Every word contributes meaning, achieving high conciseness.

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 (one parameter, no output schema), the description is adequate but bare. It does not explain what the returned list contains (e.g., table names, identifiers, metadata) or provide any nuance about the namespace scope. More detail would improve completeness without sacrificing conciseness.

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?

Schema description coverage is 0%, so the description must add meaning. It mentions 'for a given namespace', providing context for the required parameter. However, it does not specify format requirements (e.g., case sensitivity, fully qualified name) or constraints, leaving ambiguity for a single-param tool.

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 action ('provides a list'), the resource ('iceberg tables'), the source ('Iceberg catalog'), and the condition ('for a given namespace'). It effectively distinguishes this tool from siblings like get_namespaces (lists namespaces) and get_table_schema (schema of a specific table).

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 context ('for a given namespace') but does not explicitly state when to use this tool over alternatives (e.g., get_table_partitions, get_table_properties). It lacks when-not-to-use guidance or comparisons to sibling tools.

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