How to Use the Refiner MCP in LangChain

Build chains that react to user feedback using Refiner inside your LangChain agents.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Refiner MCP to LangChain

Create your Vinkius account to connect Refiner 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.

GDPR Free for Subscribers

Setup Refiner with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Chain Refiner survey data into agent logic

Pipe `list_refiner_surveys` and `list_refiner_responses` directly into your reasoning chain. LangChain agents can evaluate these inputs to decide if a user needs follow-up. Connect the output of `get_refiner_contact` to other chain nodes for automated outreach. Your agent handles the logic flow based on real-time feedback.

Automate user updates with LangChain

Trigger `identify_refiner_user` whenever your agent determines a user profile needs an update. This keeps your segments current without manual intervention. Pass data through `list_refiner_segments` so the agent understands the user's current grouping. It makes informed decisions on how to interact with different cohorts.

Track events through this MCP Server

Use `track_refiner_event` as a tool call within your LangChain pipeline to log actions as they happen. It captures user intent during the conversation flow. Monitor your API health with `check_refiner_status` to ensure your chains don't break. If the status dips, the agent can skip the tool call or alert you.

Setup guide

Set up Refiner 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 Refiner 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({
    "refiner-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 Refiner transactions"
    })
    print(result["messages"][-1].content)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Refiner. 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.

Connect Refiner now

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 Refiner MCP in LangChain

Install the necessary adapters and initialize the MultiServerMCPClient. Pass the tool list directly into your agent constructor to start executing Refiner calls within your chains.

Yes, it acts as a data source for your chain. The agent reads survey results and uses that context to determine the next step in the conversation.

Use the client session feature to maintain state. This ensures your agent remembers the user context across multiple tool calls.

Wrap your tool calls in standard error handling logic. LangSmith tracing will show you exactly where a Refiner call fails during execution.

Vinkius manages the connection via a secure endpoint token. Only your agent accesses survey responses and contact details, keeping the data isolated from other processes.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript