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ReferralHero MCP Server for LangChainGive LangChain instant access to 12 tools to Add Points, Add Subscriber, Delete Subscriber, and more

Built by Vinkius GDPR 12 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect ReferralHero 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 ReferralHero app connector for LangChain is a standout in the Industry Titans category — giving your AI agent 12 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

python
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({
        "referralhero": {
            "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 ReferralHero, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())
ReferralHero
Fully ManagedVinkius Servers
60%Token savings
High SecurityEnterprise-grade
IAMAccess control
EU AI ActCompliant
DLPData protection
V8 IsolateSandboxed
Ed25519Audit chain
<40msKill switch
Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 ReferralHero MCP Server

Connect your ReferralHero account to any AI agent and take full control of your viral growth orchestration and referral program management through natural conversation. ReferralHero provides a premier platform for building referral loops, and this integration allows you to retrieve subscriber metadata, monitor campaign leaderboards, and manage rewards directly from your chat interface.

LangChain's ecosystem of 500+ components combines seamlessly with ReferralHero through native MCP adapters. Connect 12 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

  • Campaign & List Orchestration — List all managed referral campaigns and retrieve detailed metadata, including creating and updating subscriber records programmatically.
  • Subscriber Lifecycle Management — Access and monitor individual subscriber profiles and retrieve detailed performance metadata including point balances directly from the AI interface.
  • Leaderboard & Reward Intelligence — Access real-time campaign leaderboards and monitor reward eligibility via natural language to drive program engagement.
  • Conversion & Referral Tracking — Track conversion events and attribute referrals to specific subscribers to ensure your growth loops are always synchronized.
  • Operational Monitoring — Track system activity and manage transaction metadata using simple AI commands.

The ReferralHero MCP Server exposes 12 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 12 ReferralHero tools available for LangChain

When LangChain connects to ReferralHero through Vinkius, your AI agent gets direct access to every tool listed below — spanning referralhero, viral-growth, referral-api, 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.

add_points

Add points to a subscriber

add_subscriber

Add a new subscriber to a campaign

delete_subscriber

Remove a subscriber from a campaign

get_leaderboard

Get campaign leaderboard

get_list

Get details for a specific campaign

get_rewards

Get campaign rewards

get_subscriber

Get details for a specific subscriber

list_lists

List all referral campaigns (lists)

list_subscribers

List subscribers for a campaign

list_transactions

List recent transactions

track_conversion

Track a referral conversion event

update_subscriber

Update an existing subscriber

Connect ReferralHero to LangChain via MCP

Follow these steps to wire ReferralHero into LangChain. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

01

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the agent

Save the code and run python agent.py
04

Explore tools

The agent discovers 12 tools from ReferralHero via MCP

Why Use LangChain with the ReferralHero MCP Server

LangChain provides unique advantages when paired with ReferralHero through the Model Context Protocol.

01

The largest ecosystem of integrations, chains, and agents. combine ReferralHero MCP tools with 500+ LangChain components

02

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

03

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

04

Memory and conversation persistence let agents maintain context across ReferralHero queries for multi-turn workflows

ReferralHero + LangChain Use Cases

Practical scenarios where LangChain combined with the ReferralHero MCP Server delivers measurable value.

01

RAG with live data: combine ReferralHero tool results with vector store retrievals for answers grounded in both real-time and historical data

02

Autonomous research agents: LangChain agents query ReferralHero, synthesize findings, and generate comprehensive research reports

03

Multi-tool orchestration: chain ReferralHero tools with web scrapers, databases, and calculators in a single agent run

04

Production monitoring: use LangSmith to trace every ReferralHero tool call, measure latency, and optimize your agent's performance

Example Prompts for ReferralHero in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with ReferralHero immediately.

01

"List all active referral lists in my account."

02

"Show me the leaderboard of top referrers in my active campaign with their reward balances."

03

"Send a reminder email to all campaign participants who have not shared their referral link yet."

Troubleshooting ReferralHero MCP Server with LangChain

Common issues when connecting ReferralHero to LangChain through the Vinkius, and how to resolve them.

01

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

ReferralHero + LangChain FAQ

Common questions about integrating ReferralHero MCP Server with LangChain.

01

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.
02

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.
03

Can I trace MCP tool calls in LangSmith?

Yes. All MCP tool invocations appear as traced steps in LangSmith, showing input parameters, response payloads, latency, and token usage.