Connector for the Typeform API. Provides access to forms, form responses, webhooks, workspaces, images, and themes. Supports listing and retrieving typeform resources for survey and form management workflows.

ETL, an acronym for Extract, Transform, Load, is a vital data integration process. It involves extracting data from diverse sources, transforming it into a usable format, and loading it into a database, data warehouse or data lake. This process enables meaningful data analysis, enhancing business intelligence.

ELT, standing for Extract, Load, Transform, is a modern take on the traditional ETL data integration process. In ELT, data is first extracted from various sources, loaded directly into a data warehouse, and then transformed. This approach enhances data processing speed, analytical flexibility and autonomy.

Difference between ETL and ELT?

ETL and ELT are critical data integration strategies with key differences. ETL (Extract, Transform, Load) transforms data before loading, ideal for structured data. In contrast, ELT (Extract, Load, Transform) loads data before transformation, perfect for processing large, diverse data sets in modern data warehouses. ELT is becoming the new standard as it offers a lot more flexibility and autonomy to data analysts.

Agent Connector

Connect your agents to Typeform

Production-ready access to your Typeform data with managed auth, parametric control, and the reliability your agents need to actually work.

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Installation & Usage

Get start with the Typeform connector in minutes.

[01]

Install Package

Using uv or pip

BASH

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uv pip install airbyte-agent-typeform

[02]

Import

Initialize and use

PYTHON

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from airbyte_agent_typeform import TypeformConnector
from airbyte_agent_typeform.models import TypeformAuthConfig

connector = TypeformConnector(
    auth_config=TypeformAuthConfig(
        access_token="<Personal access token from your Typeform account settings>"
    )
)

[03]

Tool

Add tools to your agent

python

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

Supported Entities & Actions

Access all your Typeform data through a unified API

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| Entity | Actions |\n|--------|---------|\n| Forms | [List](./REFERENCE.md#forms-list), [Get](./REFERENCE.md#forms-get), [Search](./REFERENCE.md#forms-search) |\n| Responses | [List](./REFERENCE.md#responses-list), [Search](./REFERENCE.md#responses-search) |\n| Webhooks | [List](./REFERENCE.md#webhooks-list), [Search](./REFERENCE.md#webhooks-search) |\n| Workspaces | [List](./REFERENCE.md#workspaces-list), [Search](./REFERENCE.md#workspaces-search) |\n| Images | [List](./REFERENCE.md#images-list), [Search](./REFERENCE.md#images-search) |\n| Themes | [List](./REFERENCE.md#themes-list), [Search](./REFERENCE.md#themes-search) |

View full reference documentation

Example Prompts

The Typeform connector is optimized to handle prompts like these

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List all my typeforms - Show me the responses for my latest form - What workspaces do I have? - List all themes in my account - Get the details of a specific form - Which forms received the most responses last month? - Find responses submitted in the last week - What forms were created this year? - Show me all forms in a specific workspace

View full reference documentation

Why Airbyte for AI Agents?

Built for production AI workloads with enterprise-grade reliability

Secure Authentication

Built-in OAuth 2.0 handling with automatic token refresh. No hard-coded credentials.

Agent-Native Design

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Structured, LLM-friendly schemas optimized for AI agent consumption with natural language query support.

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.

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Works with your favorite frameworks

Use the Salesforce connector with any AI agent framework.

LangChain

CrewAI

LlamaIndex

AutoGen

OpenAI Agents SDK

Claude Agents SDK

Frequently Asked Questions

Didn't find your answer? Please don't hesitate to reach out.

How do I authenticate with Typeform?

The Typeform connector supports personal access token authentication. You provide your access token (obtained from your Typeform account settings) directly via the TypeformAuthConfig. Alternatively, in hosted mode, credentials are stored securely in Airbyte Cloud using AirbyteAuthConfig with your client ID and client secret.

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?

Currently, the Typeform connector focuses on read operations only. Write operations such as creating new typeforms, deleting form responses, updating form settings, or sending webhook notifications 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.

Ready to connect your AI agents to Typeform?

Get started in minutes with our open-source connector.

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READ THE DOCS