Omni BI Intelligence MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Omni BI Intelligence as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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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 Omni BI Intelligence. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Omni BI Intelligence?"
)
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 Omni BI Intelligence MCP Server
Connect your Omni BI (omni.co) account to your AI agent and gain deep insights into your organization's data through natural conversation and programmatic query execution.
LlamaIndex agents combine Omni BI Intelligence tool responses with indexed documents for comprehensive, grounded answers. Connect 10 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
- Dashboard Oversight — List all available BI dashboards and retrieve detailed layout and component metadata.
- Data Model Intelligence — Access the semantic layer to list models and inspect specific field definitions and logic.
- Programmatic Queries — Execute custom queries against your data models directly from the chat and view results.
- Resource Management — Browse workspaces, folders, and projects to stay organized within your BI instance.
- Connection Monitoring — List all connected databases and data sources integrated with Omni.
- Data Export — Generate temporary export links for query results in CSV, JSON, or Excel formats.
- Deep Inspection — Fetch complete metadata for specific fields, dashboards, or data models using their unique IDs.
The Omni BI Intelligence MCP Server exposes 10 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 Omni BI Intelligence to LlamaIndex via MCP
Follow these steps to integrate the Omni BI Intelligence 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 10 tools from Omni BI Intelligence
Why Use LlamaIndex with the Omni BI Intelligence MCP Server
LlamaIndex provides unique advantages when paired with Omni BI Intelligence through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Omni BI Intelligence tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Omni BI Intelligence tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Omni BI Intelligence, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Omni BI Intelligence tools were called, what data was returned, and how it influenced the final answer
Omni BI Intelligence + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Omni BI Intelligence MCP Server delivers measurable value.
Hybrid search: combine Omni BI Intelligence real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Omni BI Intelligence 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 Omni BI Intelligence for fresh data
Analytical workflows: chain Omni BI Intelligence queries with LlamaIndex's data connectors to build multi-source analytical reports
Omni BI Intelligence MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Omni BI Intelligence to LlamaIndex via MCP:
export_query_results
Export data to file
get_dashboard_details
Get specific dashboard info
get_field_details
Get specific field info
get_model_details
Get data model metadata
list_bi_workspaces
List organization workspaces
list_dashboards
List BI dashboards
list_data_connections
List database connections
list_data_models
List Omni data models
list_resource_folders
List dashboard folders
run_omni_query
Run programmatic query
Example Prompts for Omni BI Intelligence in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Omni BI Intelligence immediately.
"List all our sales dashboards."
"Run a query on the 'Orders' model for fields 'total_price' and 'status'."
"What are the field definitions for the 'Customer Retention' model?"
Troubleshooting Omni BI Intelligence MCP Server with LlamaIndex
Common issues when connecting Omni BI Intelligence to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpOmni BI Intelligence + LlamaIndex FAQ
Common questions about integrating Omni BI Intelligence 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 Omni BI Intelligence 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 Omni BI Intelligence to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.