How to Use the Mailsoftly MCP in LangChain

Q: Can LangChain agents read Mailsoftly campaign stats?

Yes. They use getcampaigndetails and getcampaignclickdata to pull exact metrics from previous sends.

Q: Does the Mailsoftly MCP server support multi-step chains?

It fits perfectly into sequential logic. The output from createbasecontact feeds right into addcontacttolist within the same chain.

Build multi-step email marketing chains with LangChain and Mailsoftly.

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Connect Mailsoftly MCP to LangChain

Create your Vinkius account to connect Mailsoftly to LangChain and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Mailsoftly with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Sequence Audience Building

Building subscriber segments relies on `list_subscriber_collections` and `create_base_contact`. Your agent reads the available lists and inserts new emails directly into the database. LangChain turns this into a predictable pipeline. The output from finding a specific collection ID immediately becomes the input for adding the user, creating a loop that populates your lists without manual intervention.

Execute Campaigns via MCP Server

Triggering sends through the MCP Server requires exact parameters. The `send_campaign_to_all` tool handles the final stage of your marketing workflow by pushing the blast to your subscribers. You track the entire execution through LangSmith. Every tool call logs its latency and token usage, so you know exactly how long the agent took to decide on the send parameters.

Analyze Engagement Data

Pulling metrics happens via `get_campaign_click_data` and `list_sent_history`. Your ReAct agent checks what went out and calculates how many people actually clicked the links. It feeds those results back into your chain to adjust the next campaign. If open rates drop, the system catches the trend and modifies the targeting logic for the next run.

Setup guide

Set up Mailsoftly MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes Mailsoftly tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI

async with MultiServerMCPClient({
    "mailsoftly-mcp": {
        "transport": "http",
        "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    }
}) as client:
    tools = client.get_tools()

    agent = create_react_agent(
        ChatOpenAI(model="gpt-4o"),
        tools,
    )
    result = await agent.ainvoke({
        "messages": "List recent Mailsoftly transactions"
    })
    print(result["messages"][-1].content)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Mailsoftly. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Mailsoftly MCP in LangChain

Run pip install langchain-mcp-adapters langgraph. Then configure a MultiServerMCPClient with your endpoint URL and pass client.get_tools() to your agent.

Yes. They use `get_campaign_details` and `get_campaign_click_data` to pull exact metrics from previous sends.

It fits perfectly into sequential logic. The output from `create_base_contact` feeds right into `add_contact_to_list` within the same chain.

LangSmith catches the error immediately. Your agent can read the failure message and retry the operation with corrected inputs.

Emails, contact list IDs, and click metrics stay within your local environment. Vinkius runs the MCP Server in an ephemeral V8 Isolate Sandbox, meaning your API token is the only credential passed and nothing is stored.

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