Openscreen MCP Server for LlamaIndex 9 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Openscreen 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 MCP SERVER
Vinkius supports streamable HTTP and SSE.
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 Openscreen. "
"You have 9 tools available."
),
)
response = await agent.run(
"What tools are available in Openscreen?"
)
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 Openscreen MCP Server
Connect your Openscreen account to empower your AI agents with smart QR code capabilities. This server provides programmatic access to the Openscreen API for generating, managing, and tracking dynamic QR codes.
LlamaIndex agents combine Openscreen tool responses with indexed documents for comprehensive, grounded answers. Connect 9 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.
What you can do
- Dynamic QR Generation — Create trackable QR codes for physical or digital assets
- Project Organization — Manage your QR codes across multiple projects and containers
- Asset Management — Link QR codes to specific assets like URLs, SKUs, or documents
- Real-time Analytics — Monitor scan data including location, device info, and scan times
- Behavioral Control — Update the intent of existing dynamic QR codes without changing the physical code
The Openscreen MCP Server exposes 9 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.
How to Connect Openscreen to LlamaIndex via MCP
Follow these steps to integrate the Openscreen MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 9 tools from Openscreen
Why Use LlamaIndex with the Openscreen MCP Server
LlamaIndex provides unique advantages when paired with Openscreen through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Openscreen tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Openscreen tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Openscreen, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Openscreen tools were called, what data was returned, and how it influenced the final answer
Openscreen + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Openscreen MCP Server delivers measurable value.
Hybrid search: combine Openscreen real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Openscreen 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 Openscreen for fresh data
Analytical workflows: chain Openscreen queries with LlamaIndex's data connectors to build multi-source analytical reports
Openscreen MCP Tools for LlamaIndex (9)
These 9 tools become available when you connect Openscreen to LlamaIndex via MCP:
create_asset_with_qr
Create an asset and its QR code
get_asset
Get asset details
get_project
Get project details
get_qr_code
Get QR code details
list_assets
List assets in a project
list_projects
List all Openscreen projects
list_qr_codes
List QR codes in a project
list_scans
List scans for a QR code
update_qr_code_intent
Update QR code intent
Example Prompts for Openscreen in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Openscreen immediately.
"List my Openscreen projects."
Troubleshooting Openscreen MCP Server with LlamaIndex
Common issues when connecting Openscreen to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpOpenscreen + LlamaIndex FAQ
Common questions about integrating Openscreen MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect Openscreen with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Openscreen to LlamaIndex
Get your token, paste the configuration, and start using 9 tools in under 2 minutes. No API key management needed.