Build AI-powered email workflows using LangFlow's drag-and-drop interface, backed by MultiMail's email infrastructure and configurable human oversight.
LangFlow is a visual framework for building multi-agent and RAG applications with a drag-and-drop interface. It generates LangChain-compatible code from visual flows, making AI accessible to non-developers. MultiMail provides the email infrastructure that turns LangFlow's visual workflows into production email automation.
By connecting MultiMail to LangFlow, non-technical users can build email automation flows visually — triage inboxes, classify messages, compose AI-generated replies, and send them through managed mailboxes. MultiMail's oversight modes are especially important here since flow builders may not fully understand the implications of autonomous email sending.
Integrate MultiMail with LangFlow by adding custom API components that call MultiMail endpoints, or by using LangFlow's built-in HTTP request component with MultiMail's REST API.
LangFlow's drag-and-drop interface lets non-developers build email automation. Connect inbox components to classifiers to response generators to senders — all visually, with MultiMail handling the email infrastructure.
Non-technical flow builders may not anticipate edge cases in email automation. MultiMail's gated_send mode acts as a safety net, ensuring every AI-generated email is reviewed before delivery regardless of how the flow is configured.
LangFlow flows can be deployed as APIs. Combined with MultiMail, you can deploy an email processing endpoint that receives webhook notifications for new emails, processes them through your LangFlow flow, and sends responses.
LangFlow's built-in playground lets you test email flows interactively before deploying. Send test emails through MultiMail in gated_send mode to verify the flow produces appropriate responses without risking real delivery.
Combine LangFlow's visual components with MultiMail to add AI email capabilities without writing code. Drag in an LLM, connect it to MultiMail's inbox and send endpoints, and you have an intelligent email processor.
from langflow.custom import Component
from langflow.io import MessageTextInput, Output
import requests
class MultiMailSender(Component):
display_name = "MultiMail Send"
description = "Send an email through MultiMail with oversight."
inputs = [
MessageTextInput(name="api_key", display_name="API Key", required=True),
MessageTextInput(name="mailbox_id", display_name="Mailbox ID", required=True),
MessageTextInput(name="to", display_name="To", required=True),
MessageTextInput(name="subject", display_name="Subject", required=True),
MessageTextInput(name="body", display_name="Body", required=True),
]
outputs = [Output(display_name="Result", name="result", method="send")]
def send(self) -> str:
resp = requests.post(
"https://api.multimail.dev/v1/send",
headers={"Authorization": f"Bearer {self.api_key}"},
json={
"mailbox_id": self.mailbox_id,
"to": self.to,
"subject": self.subject,
"body": self.body
}
)
return str(resp.json())Create a custom LangFlow component that sends emails through MultiMail's API.
from langflow.custom import Component
from langflow.io import MessageTextInput, IntInput, Output
import requests
class MultiMailInbox(Component):
display_name = "MultiMail Inbox"
description = "Fetch recent emails from a MultiMail inbox."
inputs = [
MessageTextInput(name="api_key", display_name="API Key", required=True),
MessageTextInput(name="mailbox_id", display_name="Mailbox ID", required=True),
IntInput(name="limit", display_name="Limit", value=10),
]
outputs = [Output(display_name="Emails", name="emails", method="fetch")]
def fetch(self) -> str:
resp = requests.get(
f"https://api.multimail.dev/v1/mailboxes/{self.mailbox_id}/inbox",
headers={"Authorization": f"Bearer {self.api_key}"},
params={"limit": self.limit}
)
return str(resp.json())Create a LangFlow component that fetches emails from a MultiMail inbox.
"cm"># In LangFlow's visual editor, add an "API Request" component:
"cm">#
"cm"># 1. Drag an "API Request" component onto the canvas
"cm"># 2. Configure:
"cm"># - URL: https://api.multimail.dev/v1/mailboxes/{mailbox_id}/inbox
"cm"># - Method: GET
"cm"># - Headers: {"Authorization": "Bearer mm_live_your_api_key"}
"cm"># - Query params: {"limit": 10}
"cm">#
"cm"># 3. Connect the output to an LLM component for processing
"cm"># 4. Connect the LLM output to another API Request component
"cm"># configured for POST to https://api.multimail.dev/v1/reply
"cm">#
"cm"># This creates a visual flow:
"cm"># [Inbox Fetch] -> [LLM Classifier] -> [LLM Composer] -> [Send Reply]
"cm">#
"cm"># No custom Python code needed - just drag, connect, and configure.
"cm"># For programmatic access to the same flow:
import requests
LANGFLOW_API = "http://localhost:7860/api/v1/run/your-flow-id"
result = requests.post(LANGFLOW_API, json={
"input_value": "Process today&"cm">#039;s inbox",
"output_type": "chat"
})
print(result.json())Use LangFlow's built-in HTTP request component to call MultiMail's API without custom code.
Sign up at multimail.dev, create a mailbox, and generate an API key. Your key will start with mm_live_.
Install LangFlow and start the visual builder in your browser.
pip install langflow && langflow runEither add custom MultiMail components (MultiMailInbox, MultiMailSender) or use the built-in API Request component configured with MultiMail endpoints.
Drag components onto the canvas and connect them: Inbox Fetch -> LLM Classifier -> LLM Composer -> Email Sender. Configure each component with your MultiMail credentials.
Use LangFlow's playground to test the flow. Review pending emails in the MultiMail dashboard. Once satisfied, deploy the flow as an API endpoint.
Email infrastructure built for AI agents. Verifiable identity, graduated oversight, and a 38-tool MCP server. Formally verified in Lean 4.