How to Use the Viral Loops MCP in LangChain
Build multi-step reasoning chains for Viral Loops campaigns using LangChain.
Works with every AI agent you already use
…and any MCP-compatible client
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.
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.
Set up Viral Loops MCP in LangChain
Prerequisites
- Python 3.10+ installed
-
langchain-mcp-adapters+langgraphpackages - 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 LangChainBaseToolobjects. - 2
Connect via HTTP transport
Use
MultiServerMCPClientwith"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 Viral Loops tool calls through the MCP protocol. - 4
Run with any LLM
Swap
ChatOpenAIforChatAnthropic,ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.
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
Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.
Real-time monitoring
Live
visibility into every interaction
Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.
Built-in savings
60%
lower AI costs
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
Use it with your favorite AI tools
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Start using the Viral Loops MCP today
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