Viral Loops MCP Server for LangChain 10 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Viral Loops through the Vinkius and LangChain agents can call every tool natively — combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent
async def main():
# Your Vinkius token — get it at cloud.vinkius.com
async with MultiServerMCPClient({
"viral-loops": {
"transport": "streamable_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,
)
response = await agent.ainvoke({
"messages": [{
"role": "user",
"content": "Using Viral Loops, show me what tools are available.",
}]
})
print(response["messages"][-1].content)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Viral Loops MCP Server
Connect Viral Loops to any AI agent and supercharge your referral marketing — manage campaigns, track participants, monitor milestones, and analyze referral performance through natural conversation.
LangChain's ecosystem of 500+ components combines seamlessly with Viral Loops through native MCP adapters. Connect 10 tools via the Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures — with LangSmith tracing giving full visibility into every tool call, latency, and token cost.
What you can do
- Campaign Management — List and inspect all referral campaigns in your account
- Participant Tracking — View participants, their referral counts, and statuses
- Referral URLs — Generate and retrieve unique referral links for participants
- Milestone Monitoring — Check referral milestones and reward completion
- Campaign Statistics — Get performance metrics including total referrals and conversions
- Reward Management — View and manage reward configurations
The Viral Loops MCP Server exposes 10 tools through the Vinkius. Connect it to LangChain in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Viral Loops to LangChain via MCP
Follow these steps to integrate the Viral Loops MCP Server with LangChain.
Install dependencies
Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save the code and run python agent.py
Explore tools
The agent discovers 10 tools from Viral Loops via MCP
Why Use LangChain with the Viral Loops MCP Server
LangChain provides unique advantages when paired with Viral Loops through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents — combine Viral Loops MCP tools with 500+ LangChain components
Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step
LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging
Memory and conversation persistence let agents maintain context across Viral Loops queries for multi-turn workflows
Viral Loops + LangChain Use Cases
Practical scenarios where LangChain combined with the Viral Loops MCP Server delivers measurable value.
RAG with live data: combine Viral Loops tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Viral Loops, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Viral Loops tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Viral Loops tool call, measure latency, and optimize your agent's performance
Viral Loops MCP Tools for LangChain (10)
These 10 tools become available when you connect Viral Loops to LangChain via MCP:
create_participant
Use this when users sign up through your referral form. Add a new participant to a referral campaign
get_campaign
Use the campaign ID from list_campaigns. Get detailed information about a specific campaign
get_campaign_stats
Get performance statistics for a campaign
get_milestones
g., 5 referrals = discount, 10 referrals = free product) and their current completion status. Get referral milestones and rewards for a campaign
get_participant
Get details of a specific participant by email
get_referral_url
Get the unique referral URL for a participant
get_rewards
Get rewards configuration for a campaign
list_campaigns
Use this to discover available campaigns before querying specific ones. List all referral campaigns in your Viral Loops account
list_participants
Useful for leaderboard analysis and participant management. List all participants in a referral campaign
update_participant
Update information for an existing participant
Example Prompts for Viral Loops in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Viral Loops immediately.
"Show me all my referral campaigns."
"Get the referral URL for user@example.com in campaign 123."
"Show me the stats for campaign 123."
Troubleshooting Viral Loops MCP Server with LangChain
Common issues when connecting Viral Loops to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersViral Loops + LangChain FAQ
Common questions about integrating Viral Loops MCP Server with LangChain.
How does LangChain connect to MCP servers?
langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.Which LangChain agent types work with MCP?
Can I trace MCP tool calls in LangSmith?
Connect Viral Loops with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Viral Loops to LangChain
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.