Refiner MCP Server for LangChainGive LangChain instant access to 8 tools to Check Refiner Status, Get Refiner Contact, Identify Refiner User, and more
LangChain is the leading Python framework for composable LLM applications. Connect Refiner 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 Refiner app connector for LangChain is a standout in the Productivity category — giving your AI agent 8 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({
"refiner": {
"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 Refiner, 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 Refiner MCP Server
Connect your Refiner customer feedback account to any AI agent and simplify how you collect in-product insights, manage user segments, and monitor survey performance through natural conversation.
LangChain's ecosystem of 500+ components combines seamlessly with Refiner through native MCP adapters. Connect 8 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
- Survey Oversight — List all in-app, email, and link surveys and retrieve detailed status and response counts.
- Response Analysis — Query survey submissions with technical filters like UUIDs and date ranges to identify trends.
- Identity & Targeting — Identify users and upsert technical traits to ensure surveys reach the right audience.
- Event-Driven Feedback — Track high-fidelity user actions programmatically to trigger perfectly timed micro-surveys via AI.
- Segment Intelligence — List and query defined user segments to understand your audience distribution.
- Operational Monitoring — Check API health and verify account configurations directly from the agent.
The Refiner MCP Server exposes 8 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 8 Refiner tools available for LangChain
When LangChain connects to Refiner through Vinkius, your AI agent gets direct access to every tool listed below — spanning customer-feedback, nps-surveys, user-insights, 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.
Check API Status
Get contact details
Identify or update user
List product contacts
List survey responses
List user segments
List feedback surveys
Track user event
Connect Refiner to LangChain via MCP
Follow these steps to wire Refiner 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 Refiner MCP Server
LangChain provides unique advantages when paired with Refiner through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Refiner 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 Refiner queries for multi-turn workflows
Refiner + LangChain Use Cases
Practical scenarios where LangChain combined with the Refiner MCP Server delivers measurable value.
RAG with live data: combine Refiner tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Refiner, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Refiner tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Refiner tool call, measure latency, and optimize your agent's performance
Example Prompts for Refiner in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Refiner immediately.
"List all my feedback surveys in Refiner."
"Show me the last 5 responses for the 'NPS - Post Checkout' survey."
"Track event 'Clicked Upgrade' for user 'mike@example.com'."
Troubleshooting Refiner MCP Server with LangChain
Common issues when connecting Refiner to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersRefiner + LangChain FAQ
Common questions about integrating Refiner 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.