airbyte-agent-airtable 0.1.60

Airbyte Airtable Connector for AI platforms

Airtable

The Airtable agent connector is a Python package that equips AI agents to interact with Airtable through strongly typed, well-documented tools. It's ready to use directly in your Python app, in an agent framework, or exposed through an MCP.

Airtable is a cloud-based platform that combines the simplicity of a spreadsheet with the power of a database. This connector provides access to bases, tables, and records for data analysis and workflow automation.

Example questions

The Airtable connector is optimized to handle prompts like these.

• List all my Airtable bases
• What tables are in my first base?
• Show me the schema for tables in a base
• List records from a table in my base
• Show me recent records from a table
• What fields are in a table?
• List records where Status is 'Done' in table tblXXX
• Find records created last week in table tblXXX
• Show me records updated in the last 30 days in base appXXX

Unsupported questions

The Airtable connector isn't currently able to handle prompts like these.

• Create a new record in Airtable
• Update a record in Airtable
• Delete a record from Airtable
• Create a new table
• Modify table schema

Installation

uv pip install airbyte-agent-airtable

Usage

Connectors can run in open source or hosted mode.

Open source

In open source mode, you provide API credentials directly to the connector.

from airbyte_agent_airtable import AirtableConnector
from airbyte_agent_airtable.models import AirtableAuthConfig

connector = AirtableConnector(
    auth_config=AirtableAuthConfig(
        personal_access_token="<Airtable Personal Access Token. See https://airtable.com/developers/web/guides/personal-access-tokens>"
    )
)

@agent.tool_plain # assumes you're using Pydantic AI
@AirtableConnector.tool_utils
async def airtable_execute(entity: str, action: str, params: dict | None = None):
    return await connector.execute(entity, action, params or {})

Hosted

In hosted mode, API credentials are stored securely in Airbyte Cloud. You provide your Airbyte credentials instead. If your Airbyte client can access multiple organizations, also set organization_id.

This example assumes you've already authenticated your connector with Airbyte. See Authentication to learn more about authenticating. If you need a step-by-step guide, see the hosted execution tutorial.

from airbyte_agent_airtable import AirtableConnector, AirbyteAuthConfig

connector = AirtableConnector(
    auth_config=AirbyteAuthConfig(
        customer_name="<your_customer_name>",
        organization_id="<your_organization_id>",  # Optional for multi-org clients
        airbyte_client_id="<your-client-id>",
        airbyte_client_secret="<your-client-secret>"
    )
)

@agent.tool_plain # assumes you're using Pydantic AI
@AirtableConnector.tool_utils
async def airtable_execute(entity: str, action: str, params: dict | None = None):
    return await connector.execute(entity, action, params or {})

Full documentation

Entities and actions

This connector supports the following entities and actions. For more details, see this connector's full reference documentation.

Entity	Actions
Bases	List, Context Store Search
Tables	List, Context Store Search
Records	List, Get

Authentication

For all authentication options, see the connector's authentication documentation.

Airtable API docs

See the official Airtable API reference.

Version information

• Package version: 0.1.60
• Connector version: 1.0.8
• Generated with Connector SDK commit SHA: c5258debd165ab701252c1436d4acfb475bf92b9
• Changelog: View changelog