bootstrapping-agent

name	bootstrapping-agent
description	Wires up an Airbyte connector for use in a PydanticAI or Claude SDK agent, or any other framework via agent_tool. Generates auth config, connector initialization, and tool_utils- or agent_tool-decorated tool functions. Use when adding a connector to an agent or setting up a new agent with a connector.

Bootstrapping an Agent with an Airbyte Connector

Install the SDK

uv pip install airbyte-agent-sdk

The single airbyte-agent-sdk package ships every typed connector. Import them from airbyte_agent_sdk.connectors.{slug}. tool_utils, list_entities(), and entity_schema() are only available on typed connectors.

Core Pattern (PydanticAI)

import os
from pydantic_ai import Agent
from airbyte_agent_sdk import AirbyteAuthConfig
from airbyte_agent_sdk.connectors.stripe import StripeConnector

connector = StripeConnector(
    auth_config=AirbyteAuthConfig(
        airbyte_client_id=os.getenv("AIRBYTE_CLIENT_ID"),
        airbyte_client_secret=os.getenv("AIRBYTE_CLIENT_SECRET"),
        workspace_name=os.getenv("AIRBYTE_WORKSPACE_NAME", "default"),
    )
)

agent = Agent(
    "<provider:model>",
    system_prompt=(
        "You are a helpful assistant with access to Stripe. "
        "Use the stripe_execute tool to look up customer, invoice, and balance data. "
        "Ask for clarification if a request is ambiguous."
    ),
)

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

Always hosted mode: Use AirbyteAuthConfig with airbyte_client_id and airbyte_client_secret. Never generate local auth code.

Decorator Stacking

The framework decorator goes on top, tool_utils goes underneath:

@agent.tool_plain           # Framework registers this as a tool
@StripeConnector.tool_utils # Enriches docstring with connector capabilities
async def stripe_execute(...):

tool_utils is a @classmethod — use StripeConnector.tool_utils, not connector.tool_utils.

Automatic Retry Translation

tool_utils automatically translates retryable errors to the framework's retry signal (ModelRetry for pydantic-ai). The example above continues to work unchanged — translation happens inside tool_utils with no extra decorator needed.

Reference demo: connector-sdk/examples/demo_agent.py (mocked, no credentials needed: --mock).

Unsupported Frameworks (agent_tool)

For frameworks without a native tool_utils strategy (anything other than pydantic-ai, LangChain, OpenAI Agents, FastMCP), use agent_tool — the progressive-docs sibling of tool_utils. Decorate three functions; the role is inferred from each signature ((entity, action, ...) → execute, (section, ...) → docs, () → inspect; extra params allowed, ambiguous signatures must pass the role explicitly, e.g. agent_tool("execute")):

@StripeConnector.agent_tool(inspect_tool="stripe_inspect", docs_tool="stripe_read_docs")
async def stripe_execute(entity: str, action: str, params: dict | None = None):
    return await connector.execute(entity, action, params or {})

@StripeConnector.agent_tool()
async def stripe_inspect():
    return await connector.inspect_connector()

@StripeConnector.agent_tool()
async def stripe_read_docs(section: str | None = None):
    return await connector.read_skill_docs(section)

Register all three with the target framework. The execute docstring steers the model through inspect → docs outline → docs section → execute instead of embedding the full entity/action reference. Failures raise AirbyteToolError (from airbyte_agent_sdk import AirbyteToolError) by default — no framework auto-detection; pass framework="..." to target a supported framework's retry signal instead. The optional inspect_tool=/docs_tool= kwargs put the exact registered sibling-tool names into the execute docstring; omit them for generic phrasing.

Verify the Setup

check = await connector.check()
if check.status == "healthy":
    print(f"Connected — checked {check.checked_entity}/{check.checked_action}")
else:
    print(f"Failed: {check.error}")

Framework Detection

Detect the developer's framework from their existing imports:

• from pydantic_ai import Agent → Use PydanticAI patterns
• from anthropic import Anthropic → Use Claude SDK patterns
• If unclear, ask which framework they're using

Connector Naming Convention

All connectors ship in airbyte-agent-sdk. Import each one from airbyte_agent_sdk.connectors.{slug}:

Connector	Import	Class
stripe	airbyte_agent_sdk.connectors.stripe	StripeConnector
zendesk-support	airbyte_agent_sdk.connectors.zendesk_support	ZendeskSupportConnector
hubspot	airbyte_agent_sdk.connectors.hubspot	HubspotConnector

Hyphens in connector slugs become underscores in the submodule path.

Environment Variables

The developer needs these in their .env:

AIRBYTE_CLIENT_ID=your_client_id
AIRBYTE_CLIENT_SECRET=your_client_secret
AIRBYTE_WORKSPACE_NAME=your_workspace_name

References

• SDK API reference — full API signatures and options
• PydanticAI patterns — complete runnable examples
• Claude SDK patterns — Anthropic Python SDK examples