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How to Use the Viral Loops MCP in LangChain

Build multi-step reasoning chains for Viral Loops campaigns using LangChain.

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…and any MCP-compatible client

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LangChain

Connect Viral Loops MCP to LangChain

Create your Vinkius account to connect Viral Loops 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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Discover Campaigns and Status

You can start by finding what's available. Call `list_campaigns` to see every referral campaign ID you have set up. Once you know the ID, use `get_campaign` for the full details, or run `get_campaign_stats` to pull performance metrics. This lets your agent build a report that tracks both raw numbers and specific goals.

Managing Participants via MCP Server

The chain handles participant lifecycle management. First, use `get_participant` with an email address to get their current record. Then, if you need them to share their link, the agent calls `get_referral_url`. This sequence of tool calls lets your pipeline build a profile on the user's status.

Milestone and Reward Logic

Building complex reward logic is easy. Your chain can query milestones using `get_milestones` to see if a participant hit their discount or free product goal. It also fetches the exact rules via `get_rewards`. This lets your agent make decisions based on documented campaign rules.

Setup guide

Set up Viral Loops MCP in LangChain

Prerequisites

  • Python 3.10+ installed
  • langchain-mcp-adapters + langgraph packages
  • Active Vinkius subscription with a valid endpoint token
  1. 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. 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. 3

    Create a ReAct agent

    Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes Viral Loops tool calls through the MCP protocol.

  4. 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({
    "viral-loops-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 Viral Loops transactions"
    })
    print(result["messages"][-1].content)

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Viral Loops. 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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Real-time monitoring

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Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

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Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Viral Loops MCP in LangChain

Start by running the `list_campaigns` tool. This returns a list of every active campaign ID, allowing your agent to know which ones it needs to query next.
This MCP Server primarily handles participant records and associated email addresses. You'll be working with the user's identity data, not financial information.
Yes. Your agent can chain `get_milestones` and then pass that output to another function to determine if the user earned their discount or free product.
It does. You use the `update_participant` tool, passing in the necessary data and the unique identifier to adjust an existing record cleanly.
The system provides detailed information via the `get_campaign` tool. You get everything from the initial setup data down through the reward configuration rules.

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