How to Use the Campaigner MCP in LangChain

Build ReAct agents in LangChain that manage Campaigner email workflows and subscriber data natively.

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Connect Campaigner MCP to LangChain

Create your Vinkius account to connect Campaigner 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 Campaigner with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Chain LangChain agents to email ops

You build reasoning pipelines where one step informs the next. A ReAct agent can run `list_campaigns` to find recent sends, grab the IDs, and immediately pipe them into `get_campaign_stats` to aggregate open rates. The output feeds directly into your reporting chain without you writing custom API glue code. Because this connects through the Campaigner MCP Server, every tool call gets logged in LangSmith. You see exactly what inputs the agent decided to use when it fired off `create_subscriber`, giving you full visibility into latency and token consumption across your marketing automation steps.

Automate audience segmentation

Your multi-step workflows need context about who is receiving what. LangChain agents can execute `list_segments` and `list_publications` to map out your current contact lists. They evaluate the rules of those segments and decide where a new lead belongs. Once the agent determines the right list, it executes `get_subscriber` to check if the email already exists. If the contact is missing, the chain fires `create_subscriber` to add them, ensuring your Campaigner database stays perfectly synced with your external CRM tools.

Monitor automated workflows

Marketing teams set up complex drip sequences that often break silently. You can configure a scheduled LangChain process to run `list_workflows` and pull the current status of all automated triggers. The chain evaluates the health of these sequences against your expected baselines. If an agent detects an anomaly, it can pull specific details using `get_account_info`. This lets you build a self-healing or alerting mechanism where the AI client actively monitors your Campaigner environment and pages you when something looks wrong.

Setup guide

Set up Campaigner 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 Campaigner 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({
    "campaigner-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 Campaigner transactions"
    })
    print(result["messages"][-1].content)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Campaigner. 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.

Why Choose Vinkius

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Common questions about Campaigner MCP in LangChain

Install the langchain-mcp-adapters package. Use MultiServerMCPClient pointing to your Vinkius endpoint, call client.get_tools(), and pass the resulting tools into your ReAct agent setup.

Yes. Every MCP tool execution logs directly into LangSmith. You see the exact payload sent to create_subscriber along with the associated latency and token costs.

It does. You can combine this server with a database or CRM server in the same MultiServerMCPClient. The agent decides which system to query based on the prompt.

The agent receives the error output from the MCP connection. Because ReAct agents iterate, they can read the error message, adjust their parameters, and retry the get_campaign request automatically.

Your subscriber emails and campaign stats stay secure. Vinkius runs the server in an ephemeral V8 Isolate Sandbox. The agent only accesses the exact contact data it needs for the current chain, and the memory wipes when the session ends.

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