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Storylane MCP Server for LangChainGive LangChain instant access to 12 tools to Create Demo Link, Get Demo, Get Demo Analytics, and more

Built by Vinkius GDPR 12 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Storylane 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 Storylane app connector for LangChain is a standout in the Marketing Automation 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({
        "storylane": {
            "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 Storylane, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())
Storylane
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 Storylane MCP Server

The Storylane MCP server connects your AI agent directly to your demo infrastructure. Query demo completion rates, create personalized demo links for prospects, and sync engagement data natively.

LangChain's ecosystem of 500+ components combines seamlessly with Storylane 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.

The Storylane 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 Storylane tools available for LangChain

When LangChain connects to Storylane through Vinkius, your AI agent gets direct access to every tool listed below — spanning product-demos, interactive-content, lead-engagement, 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.

create_demo_link

Generate a new trackable demo link

get_demo

Get metadata and status for a specific demo

get_demo_analytics

Get engagement metrics for a specific demo

get_me

Get information about the current authenticated user

get_session_details

Get detailed information for a specific viewer session

get_workspace_info

Retrieve metadata about the current Storylane workspace

list_demo_links

Retrieve all active links associated with a specific demo

list_demos

List all published demos in the workspace

list_sessions

List granular session analytics for demo viewers

list_teams

List teams within the workspace

list_users

List all users and their roles in the workspace

update_demo_link

Update settings for an existing demo link

Connect Storylane to LangChain via MCP

Follow these steps to wire Storylane 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 Storylane via MCP

Why Use LangChain with the Storylane MCP Server

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

01

The largest ecosystem of integrations, chains, and agents. combine Storylane 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 Storylane queries for multi-turn workflows

Storylane + LangChain Use Cases

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

01

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

02

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

03

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

04

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

Example Prompts for Storylane in LangChain

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

01

"List all our active product demos."

02

"Create a personalized link for 'Analytics Deep Dive' for Acme Corp."

03

"Show the completion rate for the 'Platform Overview' demo."

Troubleshooting Storylane MCP Server with LangChain

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

01

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Storylane + LangChain FAQ

Common questions about integrating Storylane 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.