How to Use the Hightouch (Reverse ETL) MCP in LangChain

Q: How do I check my Hightouch (Reverse ETL) sync status in LangChain?

Use the listsyncs tool to pull all active sync configurations. You can then pipe those IDs into getsync to see the current state of any specific pipeline.

Q: Can my LangChain agent trigger alerts based on Hightouch (Reverse ETL) logs?

Yes. By calling listsyncruns within your chain, you can parse the output for failed statuses. If a failure appears, your agent can trigger an alert in your downstream notification tool.

Build chains that push data directly from your warehouse using Hightouch (Reverse ETL) and LangChain.

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Connect Hightouch (Reverse ETL) MCP to LangChain

Create your Vinkius account to connect Hightouch (Reverse ETL) 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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Setup Hightouch (Reverse ETL) with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Chain sync monitoring in LangChain

Pipe your sync status directly into your logic chains. Use `list_sync_runs` to feed real-time failure data into your agent's reasoning loop. Your agent now decides if a sync needs a retry based on the actual error codes returned by the API. It removes the guesswork from pipeline maintenance.

Dynamic Hightouch (Reverse ETL) model discovery

Give your LangChain agent access to your entire data model library. It uses `list_models` to understand which datasets are currently available for syncing. This lets your agent reference exact model IDs when you ask it to investigate data discrepancies. No more manual lookups in your dashboard.

Automated destination auditing

Connect your LangChain agent to your infrastructure map via `list_destinations`. It identifies where data flows across your stack without you writing a single line of custom code. This visibility helps your agent debug routing issues by verifying if a destination is even active. It turns your agent into an active participant in your data operations.

Setup guide

Set up Hightouch (Reverse ETL) MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
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 LangChain BaseTool objects.
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

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes Hightouch (Reverse ETL) tool calls through the MCP protocol.
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({
    "hightouch-reverse-etl-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 Hightouch (Reverse ETL) transactions"
    })
    print(result["messages"][-1].content)

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Common questions about Hightouch (Reverse ETL) MCP in LangChain

Use the `list_syncs` tool to pull all active sync configurations. You can then pipe those IDs into `get_sync` to see the current state of any specific pipeline.

Yes. By calling `list_sync_runs` within your chain, you can parse the output for failed statuses. If a failure appears, your agent can trigger an alert in your downstream notification tool.

You bet. The MCP server exposes your sources and models as tools. Your agent can call `list_sources` to map out your infrastructure before it touches a single sync.

Vinkius handles the auth handshake for you. You just provide the endpoint token and the server manages the secure connection to your account.

The server only touches your pipeline metadata, such as sync configurations, model definitions, and run logs. It never accesses the raw PII stored within your actual data rows.

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