Porsline MCP Server for LangChainGive LangChain instant access to 12 tools to Check Porsline Status, Create Folder, Create Survey, and more
LangChain is the leading Python framework for composable LLM applications. Connect Porsline 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 Porsline app connector for LangChain is a standout in the Customer Support 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
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({
"porsline": {
"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 Porsline, 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 Porsline MCP Server
Connect your Porsline account to any AI agent and simplify your survey creation, response tracking, and feedback orchestration through natural conversation.
LangChain's ecosystem of 500+ components combines seamlessly with Porsline 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
- Survey Management — List all surveys, retrieve detailed metadata, status, and summary for each form
- Response Tracking — Access individual responses and answers to stay on top of your user feedback
- Live Reporting — Query aggregate metrics and summary reports for any survey to understand performance
- Folder Coordination — List organizational folders to manage your survey distribution and project structure
- Direct Insights — Monitor your survey pipeline and engagement metrics directly from your agent
The Porsline 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 Porsline tools available for LangChain
When LangChain connects to Porsline through Vinkius, your AI agent gets direct access to every tool listed below — spanning feedback-collection, form-builder, data-reporting, 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
Create a folder
Create a survey
Duplicate a survey
Export responses
Get survey report
Get response details
Get survey details
List folders
List questions
List responses
List surveys
Connect Porsline to LangChain via MCP
Follow these steps to wire Porsline 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 Porsline MCP Server
LangChain provides unique advantages when paired with Porsline through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Porsline 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 Porsline queries for multi-turn workflows
Porsline + LangChain Use Cases
Practical scenarios where LangChain combined with the Porsline MCP Server delivers measurable value.
RAG with live data: combine Porsline tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Porsline, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Porsline tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Porsline tool call, measure latency, and optimize your agent's performance
Example Prompts for Porsline in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Porsline immediately.
"List all my surveys in Porsline."
"Show me all active surveys and their response rates for the current quarter."
"Get the detailed results and analytics for the Customer Satisfaction Q2 survey."
Troubleshooting Porsline MCP Server with LangChain
Common issues when connecting Porsline to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersPorsline + LangChain FAQ
Common questions about integrating Porsline 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.