How do I get an Omni BI API Key?

Log in to your Omni instance, navigate to user settings or organization settings, and look for the API Tokens section to generate a new token.

Can I run raw SQL queries?

This implementation uses the `run_omni_query` tool which interacts with your defined data models (semantic layer). Raw SQL access depends on your specific model configuration in Omni.

What formats are supported for data export?

The `export_query_results` tool supports CSV, JSON, and XLSX formats. You will receive a temporary URL to download the requested file.

Omni BI Intelligence MCP Server for CrewAI 10 tools — connect in under 2 minutes

Name: Omni BI Intelligence
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to Omni BI Intelligence through Vinkius, pass the Edge URL in the `mcps` parameter and every Omni BI Intelligence tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Omni BI Intelligence Specialist",
    goal="Help users interact with Omni BI Intelligence effectively",
    backstory=(
        "You are an expert at leveraging Omni BI Intelligence tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Omni BI Intelligence "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 10 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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* 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.

When paired with CrewAI, Omni BI Intelligence becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Omni BI Intelligence tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

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 CrewAI 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 CrewAI via MCP

Follow these steps to integrate the Omni BI Intelligence MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 10 tools from Omni BI Intelligence

Why Use CrewAI with the Omni BI Intelligence MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Omni BI Intelligence through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Omni BI Intelligence + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Omni BI Intelligence MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Omni BI Intelligence for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Omni BI Intelligence, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Omni BI Intelligence tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Omni BI Intelligence against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Omni BI Intelligence MCP Tools for CrewAI (10)

These 10 tools become available when you connect Omni BI Intelligence to CrewAI 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 CrewAI

Ready-to-use prompts you can give your CrewAI 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 CrewAI

Common issues when connecting Omni BI Intelligence to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Omni BI Intelligence + CrewAI FAQ

Common questions about integrating Omni BI Intelligence MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.