Sendgrid

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

The Sendgrid agent connector is a Python package that equips AI agents to interact with Sendgrid 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.

Connector for the Twilio SendGrid v3 API. Provides read access to marketing campaigns, contacts, lists, segments, single sends, transactional templates, and suppression management (bounces, blocks, spam reports, invalid emails, global suppressions, suppression groups, and suppression group members).

Example prompts

The Sendgrid connector is optimized to handle prompts like these.

List all marketing contacts
Get the details of a specific contact
Show me all marketing lists
List all transactional templates
Show all single sends
List all bounced emails
Show all blocked email addresses
List all spam reports
Show all suppression groups
How many contacts are in each marketing list?
Which single sends were scheduled in the last month?
What are the most common bounce reasons?
Show me contacts created in the last 7 days

Unsupported prompts

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

Send an email
Create a new contact
Delete a bounce record
Update a marketing list

Entities and actions

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

Entity	Actions
Contacts	List, Get, Context Store Search
Lists	List, Get, Context Store Search
Segments	List, Get, Context Store Search
Campaigns	List, Context Store Search
Singlesends	List, Get, Context Store Search
Templates	List, Get, Context Store Search
Singlesend Stats	List, Context Store Search
Bounces	List, Context Store Search
Blocks	List, Context Store Search
Spam Reports	List
Invalid Emails	List, Context Store Search
Global Suppressions	List, Context Store Search
Suppression Groups	List, Get, Context Store Search
Suppression Group Members	List, Context Store Search

Sendgrid API docs

See the official Sendgrid API reference.

SDK installation

uv pip install airbyte-agent-sdk

SDK usage

Connectors can run in hosted or open source mode.

Hosted

In hosted mode, API credentials are stored securely in Airbyte Agents. 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.

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

Pydantic AI
LangChain
OpenAI Agents
FastMCP

Pydantic AI
from pydantic_ai import Agent
from airbyte_agent_sdk import connect
from airbyte_agent_sdk.connectors.sendgrid import SendgridConnector

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

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

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

LangChain
from langchain_core.tools import tool
from airbyte_agent_sdk import connect
from airbyte_agent_sdk.connectors.sendgrid import SendgridConnector

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

@tool
@SendgridConnector.tool_utils
async def sendgrid_execute(entity: str, action: str, params: dict | None = None):
    """Execute Sendgrid 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
from agents import Agent, function_tool
from airbyte_agent_sdk import connect
from airbyte_agent_sdk.connectors.sendgrid import SendgridConnector

connector = connect("sendgrid", 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)
@SendgridConnector.tool_utils(framework="openai_agents")
async def sendgrid_execute(entity: str, action: str, params: dict | None = None):
    """Execute Sendgrid 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="Sendgrid Assistant", tools=[sendgrid_execute])

FastMCP
from fastmcp import FastMCP
from airbyte_agent_sdk import connect
from airbyte_agent_sdk.connectors.sendgrid import SendgridConnector

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

mcp = FastMCP("Sendgrid Agent")

@mcp.tool
@SendgridConnector.tool_utils
async def sendgrid_execute(entity: str, action: str, params: dict | None = None):
    """Execute Sendgrid 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
LangChain
OpenAI Agents
FastMCP

Pydantic AI
from pydantic_ai import Agent
from airbyte_agent_sdk.connectors.sendgrid import SendgridConnector
from airbyte_agent_sdk.types import AirbyteAuthConfig

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

LangChain
from langchain_core.tools import tool
from airbyte_agent_sdk.connectors.sendgrid import SendgridConnector
from airbyte_agent_sdk.types import AirbyteAuthConfig

connector = SendgridConnector(
    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
@SendgridConnector.tool_utils
async def sendgrid_execute(entity: str, action: str, params: dict | None = None):
    """Execute Sendgrid 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
from agents import Agent, function_tool
from airbyte_agent_sdk.connectors.sendgrid import SendgridConnector
from airbyte_agent_sdk.types import AirbyteAuthConfig

connector = SendgridConnector(
    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)
@SendgridConnector.tool_utils(framework="openai_agents")
async def sendgrid_execute(entity: str, action: str, params: dict | None = None):
    """Execute Sendgrid 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="Sendgrid Assistant", tools=[sendgrid_execute])

FastMCP
from fastmcp import FastMCP
from airbyte_agent_sdk.connectors.sendgrid import SendgridConnector
from airbyte_agent_sdk.types import AirbyteAuthConfig

connector = SendgridConnector(
    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("Sendgrid Agent")

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

Open source

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

Pydantic AI
LangChain
OpenAI Agents
FastMCP

Pydantic AI
from pydantic_ai import Agent
from airbyte_agent_sdk.connectors.sendgrid import SendgridConnector
from airbyte_agent_sdk.connectors.sendgrid.models import SendgridAuthConfig

connector = SendgridConnector(
    auth_config=SendgridAuthConfig(
        api_key="<Your SendGrid API key (generated at https://app.sendgrid.com/settings/api_keys)>"
    )
)

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

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

LangChain
from langchain_core.tools import tool
from airbyte_agent_sdk.connectors.sendgrid import SendgridConnector
from airbyte_agent_sdk.connectors.sendgrid.models import SendgridAuthConfig

connector = SendgridConnector(
    auth_config=SendgridAuthConfig(
        api_key="<Your SendGrid API key (generated at https://app.sendgrid.com/settings/api_keys)>"
    )
)

@tool
@SendgridConnector.tool_utils
async def sendgrid_execute(entity: str, action: str, params: dict | None = None):
    """Execute Sendgrid 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
from agents import Agent, function_tool
from airbyte_agent_sdk.connectors.sendgrid import SendgridConnector
from airbyte_agent_sdk.connectors.sendgrid.models import SendgridAuthConfig

connector = SendgridConnector(
    auth_config=SendgridAuthConfig(
        api_key="<Your SendGrid API key (generated at https://app.sendgrid.com/settings/api_keys)>"
    )
)

# strict_mode=False because `params: dict` is permissive and the default strict
# JSON schema rejects objects with additionalProperties.
@function_tool(strict_mode=False)
@SendgridConnector.tool_utils(framework="openai_agents")
async def sendgrid_execute(entity: str, action: str, params: dict | None = None):
    """Execute Sendgrid 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="Sendgrid Assistant", tools=[sendgrid_execute])

FastMCP
from fastmcp import FastMCP
from airbyte_agent_sdk.connectors.sendgrid import SendgridConnector
from airbyte_agent_sdk.connectors.sendgrid.models import SendgridAuthConfig

connector = SendgridConnector(
    auth_config=SendgridAuthConfig(
        api_key="<Your SendGrid API key (generated at https://app.sendgrid.com/settings/api_keys)>"
    )
)

mcp = FastMCP("Sendgrid Agent")

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

Authentication

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

Version information

Connector version: 1.0.3

Example prompts​

Unsupported prompts​

Entities and actions​

Sendgrid API docs​

SDK installation​

SDK usage​

Hosted​

Open source​

Authentication​

Version information​