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onimsha

Airtable OAuth MCP Server

by onimsha

describe_table

Retrieve detailed metadata about an Airtable table, including its structure and fields, to understand its data organization and schema.

Instructions

Get detailed information about a specific table

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
base_idYesThe Airtable base ID
table_idYesThe table ID or name

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • Handler function that implements the describe_table tool logic: authenticates client, fetches base schema, locates the table, and returns its details including fields and views. Also serves as registration via @self.mcp.tool decorator.
    @self.mcp.tool(description="Get detailed information about a specific table")
    async def describe_table(
        base_id: Annotated[str, Field(description="The Airtable base ID")],
        table_id: Annotated[str, Field(description="The table ID or name")],
    ) -> dict[str, Any]:
        """Get detailed information about a specific table including all fields."""
        client = await self._get_authenticated_client()
        schema = await client.get_base_schema(base_id)
    
        # Find the specific table
        table = next(
            (t for t in schema.tables if t.id == table_id or t.name == table_id),
            None,
        )
    
        if not table:
            raise AirtableAPIError(
                f"Table '{table_id}' not found in base '{base_id}'"
            )
    
        return {
            "id": table.id,
            "name": table.name,
            "description": table.description,
            "primaryFieldId": table.primary_field_id,
            "fields": [
                {
                    "id": field.id,
                    "name": field.name,
                    "type": field.type,
                    "description": field.description,
                    "options": field.options,
                }
                for field in table.fields
            ],
            "views": table.views,
        }
  • Pydantic schema defining input arguments for describe_table tool (base_id and table_id), though used primarily in tests.
    class DescribeTableArgs(BaseArgs):
        """Arguments for describe_table tool."""
    
        base_id: str = Field(description="The Airtable base ID")
        table_id: str = Field(description="The table ID or name")
Behavior2/5

Does 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. While 'Get detailed information' implies a read operation, it doesn't specify whether this requires authentication, what format the information returns in, potential rate limits, or error conditions. For a tool with zero annotation coverage, this leaves significant behavioral gaps unaddressed.

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 directly states the tool's purpose without unnecessary words. It's appropriately sized for a simple read operation and front-loads the core functionality. Every word earns its place in this concise formulation.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's relative simplicity (2 required parameters), 100% schema coverage, and the presence of an output schema (which handles return values), the description is reasonably complete. It states the core purpose clearly. However, it could better address behavioral aspects given the lack of annotations, and usage guidance is minimal.

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 description adds no parameter-specific information beyond what's already in the schema (which has 100% coverage). It doesn't explain what 'detailed information' includes, how table_id can be specified (ID vs name), or provide examples. With complete schema documentation, the baseline is 3, but the description doesn't enhance parameter understanding.

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 verb 'Get' and resource 'detailed information about a specific table', making the purpose understandable. It distinguishes from siblings like list_tables (which lists tables) and get_record (which gets records), but doesn't explicitly contrast with them. The description is specific enough to understand what the tool does without being tautological.

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 this tool is appropriate versus list_tables (for listing tables) or get_record (for getting record data), nor does it provide any context about prerequisites or typical use cases. The agent must infer usage from the tool name and description 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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