ReferralCandy MCP Server for LangChainGive LangChain instant access to 16 tools to Check Referralcandy Status, Get Campaign, Get Referral, and more
LangChain is the leading Python framework for composable LLM applications. Connect ReferralCandy through 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 App Connector for LangChain
The ReferralCandy app connector for LangChain is a standout in the Marketing Automation category — giving your AI agent 16 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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({
"referralcandy": {
"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 ReferralCandy, 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 ReferralCandy MCP Server
Give your AI agent full programmatic control over your ReferralCandy ecosystem. With 16 tools tailored for referral marketing, your agent can instantly track referrals by period, register attributed purchases, identify top advocates, monitor pending rewards, manage campaigns, and send referral invitations directly from your natural language workspace.
LangChain's ecosystem of 500+ components combines seamlessly with ReferralCandy through native MCP adapters. Connect 16 tools via 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
- List and filter referrals by period
- Register purchases to trigger rewards
- Identify and manage top-performing advocates
- Monitor pending referral payouts
- Configure campaigns and send invites
- Access overall program statistics
Who is it for?
Designed for marketing teams, e-commerce operators, and growth hackers who need instant, conversational access to affiliate and referral performance metrics.The ReferralCandy MCP Server exposes 16 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.
All 16 ReferralCandy tools available for LangChain
When LangChain connects to ReferralCandy through Vinkius, your AI agent gets direct access to every tool listed below — spanning referral-marketing, affiliates, loyalty, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Verify connectivity
Get campaign details
Get referral details
Get advocate profile
Get program stats
Get top advocates
List campaigns
List sent invites
List pending rewards
List referred purchases
List all referrals
List referrals by period
List all advocates
List all rewards
Register a purchase
Send a referral invite
Connect ReferralCandy to LangChain via MCP
Follow these steps to wire ReferralCandy into LangChain. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install langchain langchain-mcp-adapters langgraph langchain-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
python agent.pyExplore tools
Why Use LangChain with the ReferralCandy MCP Server
LangChain provides unique advantages when paired with ReferralCandy through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine ReferralCandy 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 ReferralCandy queries for multi-turn workflows
ReferralCandy + LangChain Use Cases
Practical scenarios where LangChain combined with the ReferralCandy MCP Server delivers measurable value.
RAG with live data: combine ReferralCandy tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query ReferralCandy, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain ReferralCandy tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every ReferralCandy tool call, measure latency, and optimize your agent's performance
Example Prompts for ReferralCandy in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with ReferralCandy immediately.
"Can you find the top referrers in my ReferralCandy program for the last month?"
"Register a purchase of $150.00 for order #90210 by customer@example.com."
"List all pending referral rewards that need to be processed this week."
Troubleshooting ReferralCandy MCP Server with LangChain
Common issues when connecting ReferralCandy to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersReferralCandy + LangChain FAQ
Common questions about integrating ReferralCandy 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.