Give agents tools for secure, real-time access to fetch, search, write, and sync across every system, with replication, entity mapping, and auth built-in.
About this Connector
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.
CRM
Sales Analytics
Customer Data
Version Information
Package version
0.1.35
Connector version
1.0.5
SDK commit
cb4380e76ac5cbc67b9089f94522be1bbe9f8d73
Support Open Source
Check us out on Github and join the Airbyte community
Installation & Usage
1
Install Package
Using uv or pip
bash
uv pip install airbyte-agent-airtable
2
Import
Initialize and use
python
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>"
)
)3
Tool
Add tools to your agent
python
@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 {})Supported Entities & Actions
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| Entity | Actions |\n|--------|---------|\n| Bases | [List](./REFERENCE.md#bases-list), [Search](./REFERENCE.md#bases-search) |\n| Tables | [List](./REFERENCE.md#tables-list), [Search](./REFERENCE.md#tables-search) |\n| Records | [List](./REFERENCE.md#records-list), [Get](./REFERENCE.md#records-get) |
Example Prompts
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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
Why Airbyte for AI Agents?
Built for production AI workloads with enterprise-grade reliability
Agent-Native Design
Structured, LLM-friendly schemas optimized for AI agent consumption with natural language query support.
Secure Authentication
Built-in OAuth 2.0 handling with automatic token refresh. No hard-coded credentials.
Production Ready
Battle-tested connectors with comprehensive error handling, logging, and retry logic.
Open Source
Fully open source under the MIT license. Contribute, customize, and extend freely.
Works with your favorite frameworks
🦜
LangChain
🦙
LlamaIndex
🤖
CrewAI
⚡
AutoGen
🧠
OpenAI Agents SDK
🔮
Claude Agents SDK
Frequently Asked Questions
Didn't find your answer? Please don't hesitate to reach out.
The Airtable connector supports authentication via a Personal Access Token (provided directly in open source mode) or via Airbyte Cloud credentials (client ID and client secret) in hosted mode.
Can I use this connector with any AI agent framework?
The connector is compatible with any Python-based AI agent framework including LangChain, LlamaIndex, CrewAI, Pydantic AI, and custom implementations.
Does this connector support write operations?
No, the Airtable connector currently only supports read operations. Write operations such as creating, updating, or deleting records, creating tables, or modifying table schemas are not supported at this time.
How is this different from the Airbyte data connector?
Agent connectors are specifically designed for AI agents and LLM applications. They provide natural language interfaces, optimized response formats, and seamless integration with agent frameworks, unlike traditional ETL-focused connectors.
Will there be a platform for agent connectors?
The hosted version with secure credential storage through Airbyte Cloud is already available. See the hosted usage section in the documentation for setup instructions.
