Umbrellar MCP Server for LlamaIndexGive LlamaIndex instant access to 12 tools to Check Product Eligibility, Create Claim, Get Claim, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Umbrellar 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 Umbrellar app connector for LlamaIndex is a standout in the Developer Tools 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 Umbrellar. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in Umbrellar?"
)
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 Umbrellar MCP Server
The Umbrellar MCP server provides a direct conversational link to your cloud infrastructure. Query server status, check domain availability, and monitor your managed services directly via AI.
LlamaIndex agents combine Umbrellar 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 Umbrellar 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 Umbrellar tools available for LlamaIndex
When LlamaIndex connects to Umbrellar through Vinkius, your AI agent gets direct access to every tool listed below — spanning cloud-hosting, domain-management, managed-services, 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 if a product is eligible for warranty coverage
Submit a new warranty claim
Get details for a specific warranty claim
Get details for a specific warranty policy
Get details for a specific warranty plan
List all warranty claims
List all warranty policies
List all available warranty plans
Register a product for OEM or manufacturer warranty
Sync products between Shopify and Umbrellar
Update an existing warranty claim
Validate if a policy exists by matching ID and order name
Connect Umbrellar to LlamaIndex via MCP
Follow these steps to wire Umbrellar 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 Umbrellar MCP Server
LlamaIndex provides unique advantages when paired with Umbrellar through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Umbrellar tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Umbrellar tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Umbrellar, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Umbrellar tools were called, what data was returned, and how it influenced the final answer
Umbrellar + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Umbrellar MCP Server delivers measurable value.
Hybrid search: combine Umbrellar real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Umbrellar 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 Umbrellar for fresh data
Analytical workflows: chain Umbrellar queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Umbrellar in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Umbrellar immediately.
"List all my active cloud servers."
"Check the expiration date for the domain 'vinkius.com'."
"Show the resource usage for 'Web-Node-1'."
Troubleshooting Umbrellar MCP Server with LlamaIndex
Common issues when connecting Umbrellar to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpUmbrellar + LlamaIndex FAQ
Common questions about integrating Umbrellar MCP Server with LlamaIndex.