Storylane MCP Server for LlamaIndexGive LlamaIndex instant access to 12 tools to Create Demo Link, Get Demo, Get Demo Analytics, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Storylane as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
Ask AI about this App Connector for LlamaIndex
The Storylane app connector for LlamaIndex 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
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to Storylane. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in Storylane?"
)
print(response)
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 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.
LlamaIndex agents combine Storylane tool responses with indexed documents for comprehensive, grounded answers. Connect 12 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
The Storylane MCP Server exposes 12 tools through the Vinkius. Connect it to LlamaIndex 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 LlamaIndex
When LlamaIndex 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.
Generate a new trackable demo link
Get metadata and status for a specific demo
Get engagement metrics for a specific demo
Get information about the current authenticated user
Get detailed information for a specific viewer session
Retrieve metadata about the current Storylane workspace
Retrieve all active links associated with a specific demo
List all published demos in the workspace
List granular session analytics for demo viewers
List teams within the workspace
List all users and their roles in the workspace
Update settings for an existing demo link
Connect Storylane to LlamaIndex via MCP
Follow these steps to wire Storylane into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install llama-index-tools-mcp llama-index-llms-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use LlamaIndex with the Storylane MCP Server
LlamaIndex provides unique advantages when paired with Storylane through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Storylane tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Storylane tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Storylane, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Storylane tools were called, what data was returned, and how it influenced the final answer
Storylane + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Storylane MCP Server delivers measurable value.
Hybrid search: combine Storylane real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Storylane to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Storylane for fresh data
Analytical workflows: chain Storylane queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Storylane in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Storylane immediately.
"List all our active product demos."
"Create a personalized link for 'Analytics Deep Dive' for Acme Corp."
"Show the completion rate for the 'Platform Overview' demo."
Troubleshooting Storylane MCP Server with LlamaIndex
Common issues when connecting Storylane to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpStorylane + LlamaIndex FAQ
Common questions about integrating Storylane MCP Server with LlamaIndex.