Asana authentication

This connector is optimized for AI agents. For the data replication connector, see Asana.

This page documents the authentication and configuration options for the Asana agent connector.

Hosted mode (most cases)

In hosted mode, create the connector through the Airbyte Agent CLI or API, then execute operations using the CLI, Python SDK, or API. If you need a step-by-step guide, see the developer quickstart.

OAuth

Use the CLI for hosted OAuth connector creation when possible. It opens the hosted setup flow and avoids passing connector secrets through the command line:

airbyte-agent login
airbyte-agent connectors create --json '{
  "workspace": "<your_workspace_name>",
  "name": "asana"
}'

For API-first use cases, create a connector with OAuth credentials directly.

credentials fields you need:

Field Name	Type	Required	Description
access_token	str	No	OAuth access token for API requests
refresh_token	str	Yes	OAuth refresh token for automatic token renewal
client_id	str	No	Connected App Client ID
client_secret	str	No	Connected App Client Secret

Example request:

curl -X POST "https://api.airbyte.ai/api/v1/integrations/connectors" \
  -H "Authorization: Bearer <YOUR_BEARER_TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{
    "workspace_name": "<WORKSPACE_NAME>",
    "connector_type": "Asana",
    "name": "My Asana Connector",
    "credentials": {
      "access_token": "<OAuth access token for API requests>",
      "refresh_token": "<OAuth refresh token for automatic token renewal>",
      "client_id": "<Connected App Client ID>",
      "client_secret": "<Connected App Client Secret>"
    }
  }'

Token

Create a connector with Token credentials.

credentials fields you need:

Field Name	Type	Required	Description
token	str	Yes	Your Asana Personal Access Token. Generate one at https://app.asana.com/0/my-apps

Example request:

curl -X POST "https://api.airbyte.ai/api/v1/integrations/connectors" \
  -H "Authorization: Bearer <YOUR_BEARER_TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{
    "workspace_name": "<WORKSPACE_NAME>",
    "connector_type": "Asana",
    "name": "My Asana Connector",
    "credentials": {
      "token": "<Your Asana Personal Access Token. Generate one at https://app.asana.com/0/my-apps>"
    }
  }'

Execution

After creating the connector, execute operations using the CLI, Python SDK, or API. If your Airbyte client can access multiple organizations, set the default organization with airbyte-agent organizations use, include organization_id in AirbyteAuthConfig, or include X-Organization-Id in raw API calls.

CLI

Authenticate with Airbyte:

airbyte-agent login

Create the connector. The CLI opens the hosted setup flow:

airbyte-agent connectors create --json '{
  "workspace": "<your_workspace_name>",
  "name": "asana"
}'

Describe the connector to see its supported entities and actions:

airbyte-agent connectors describe --json '{
  "workspace": "<your_workspace_name>",
  "name": "asana"
}'

Execute an action:

airbyte-agent connectors execute --json '{
  "workspace": "<your_workspace_name>",
  "name": "asana",
  "entity": "<entity>",
  "action": "<action>",
  "params": {}
}'

Python SDK

The connect() factory returns a fully typed AsanaConnector and reads AIRBYTE_CLIENT_ID / AIRBYTE_CLIENT_SECRET from the environment:

Pydantic AI

Pydantic AI

from pydantic_ai import Agent
from airbyte_agent_sdk import connect
from airbyte_agent_sdk.connectors.asana import AsanaConnector

connector = connect("asana", workspace_name="<your_workspace_name>")

agent = Agent("openai:gpt-4o")

@agent.tool_plain
@AsanaConnector.tool_utils
async def asana_execute(entity: str, action: str, params: dict | None = None):
    return await connector.execute(entity, action, params or {})

LangChain

LangChain

from langchain_core.tools import tool
from airbyte_agent_sdk import connect
from airbyte_agent_sdk.connectors.asana import AsanaConnector

connector = connect("asana", workspace_name="<your_workspace_name>")

@tool
@AsanaConnector.tool_utils
async def asana_execute(entity: str, action: str, params: dict | None = None):
    """Execute Asana connector operations."""
    result = await connector.execute(entity, action, params or {})
    # connector.execute returns a Pydantic envelope for typed actions; fall back to raw data otherwise.
    return result.model_dump(mode="json") if hasattr(result, "model_dump") else result

OpenAI Agents

OpenAI Agents

from agents import Agent, function_tool
from airbyte_agent_sdk import connect
from airbyte_agent_sdk.connectors.asana import AsanaConnector

connector = connect("asana", workspace_name="<your_workspace_name>")

# strict_mode=False because `params: dict` is permissive and the default strict
# JSON schema rejects objects with additionalProperties.
@function_tool(strict_mode=False)
@AsanaConnector.tool_utils(framework="openai_agents")
async def asana_execute(entity: str, action: str, params: dict | None = None):
    """Execute Asana connector operations."""
    result = await connector.execute(entity, action, params or {})
    return result.model_dump(mode="json") if hasattr(result, "model_dump") else result

agent = Agent(name="Asana Assistant", tools=[asana_execute])

FastMCP

FastMCP

from fastmcp import FastMCP
from airbyte_agent_sdk import connect
from airbyte_agent_sdk.connectors.asana import AsanaConnector

connector = connect("asana", workspace_name="<your_workspace_name>")

mcp = FastMCP("Asana Agent")

@mcp.tool
@AsanaConnector.tool_utils
async def asana_execute(entity: str, action: str, params: dict | None = None):
    """Execute Asana connector operations."""
    result = await connector.execute(entity, action, params or {})
    return result.model_dump(mode="json") if hasattr(result, "model_dump") else result

Or pass credentials explicitly (equivalent, useful when you're not loading them from the environment): Pydantic AI

Pydantic AI

Pydantic AI

from pydantic_ai import Agent
from airbyte_agent_sdk.connectors.asana import AsanaConnector
from airbyte_agent_sdk.types import AirbyteAuthConfig

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

agent = Agent("openai:gpt-4o")

@agent.tool_plain
@AsanaConnector.tool_utils
async def asana_execute(entity: str, action: str, params: dict | None = None):
    return await connector.execute(entity, action, params or {})

LangChain

LangChain

from langchain_core.tools import tool
from airbyte_agent_sdk.connectors.asana import AsanaConnector
from airbyte_agent_sdk.types import AirbyteAuthConfig

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

@tool
@AsanaConnector.tool_utils
async def asana_execute(entity: str, action: str, params: dict | None = None):
    """Execute Asana connector operations."""
    result = await connector.execute(entity, action, params or {})
    # connector.execute returns a Pydantic envelope for typed actions; fall back to raw data otherwise.
    return result.model_dump(mode="json") if hasattr(result, "model_dump") else result

OpenAI Agents

OpenAI Agents

from agents import Agent, function_tool
from airbyte_agent_sdk.connectors.asana import AsanaConnector
from airbyte_agent_sdk.types import AirbyteAuthConfig

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

# strict_mode=False because `params: dict` is permissive and the default strict
# JSON schema rejects objects with additionalProperties.
@function_tool(strict_mode=False)
@AsanaConnector.tool_utils(framework="openai_agents")
async def asana_execute(entity: str, action: str, params: dict | None = None):
    """Execute Asana connector operations."""
    result = await connector.execute(entity, action, params or {})
    return result.model_dump(mode="json") if hasattr(result, "model_dump") else result

agent = Agent(name="Asana Assistant", tools=[asana_execute])

FastMCP

FastMCP

from fastmcp import FastMCP
from airbyte_agent_sdk.connectors.asana import AsanaConnector
from airbyte_agent_sdk.types import AirbyteAuthConfig

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

mcp = FastMCP("Asana Agent")

@mcp.tool
@AsanaConnector.tool_utils
async def asana_execute(entity: str, action: str, params: dict | None = None):
    """Execute Asana connector operations."""
    result = await connector.execute(entity, action, params or {})
    return result.model_dump(mode="json") if hasattr(result, "model_dump") else result

API

curl -X POST 'https://api.airbyte.ai/api/v1/integrations/connectors/<connector_id>/execute' \
  -H 'Authorization: Bearer <YOUR_BEARER_TOKEN>' \
  -H 'X-Organization-Id: <YOUR_ORGANIZATION_ID>' \
  -H 'Content-Type: application/json' \
  -d '{"entity": "<entity>", "action": "<action>", "params": {}}'

Open source mode

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

OAuth

credentials fields you need:

Field Name	Type	Required	Description
access_token	str	No	OAuth access token for API requests
refresh_token	str	Yes	OAuth refresh token for automatic token renewal
client_id	str	No	Connected App Client ID
client_secret	str	No	Connected App Client Secret

Example request:

from airbyte_agent_sdk.connectors.asana import AsanaConnector
from airbyte_agent_sdk.connectors.asana.models import AsanaOauth2AuthConfig

connector = AsanaConnector(
    auth_config=AsanaOauth2AuthConfig(
        access_token="<OAuth access token for API requests>",
        refresh_token="<OAuth refresh token for automatic token renewal>",
        client_id="<Connected App Client ID>",
        client_secret="<Connected App Client Secret>"
    )
)

Token

credentials fields you need:

Field Name	Type	Required	Description
token	str	Yes	Your Asana Personal Access Token. Generate one at https://app.asana.com/0/my-apps

Example request:

from airbyte_agent_sdk.connectors.asana import AsanaConnector
from airbyte_agent_sdk.connectors.asana.models import AsanaPersonalAccessTokenAuthConfig

connector = AsanaConnector(
    auth_config=AsanaPersonalAccessTokenAuthConfig(
        token="<Your Asana Personal Access Token. Generate one at https://app.asana.com/0/my-apps>"
    )
)