# Omni BI Intelligence MCP > Omni BI Intelligence connects your AI agent directly to your organization's business intelligence data. You can list dashboards, inspect complex data models, and run programmatic queries using plain language—no need to open the dashboard UI or write SQL. ## Overview - **Category:** data-analytics - **Price:** Free - **Tags:** data-exploration, semantic-layer, metrics-tracking, dashboard-management, query-execution ## Description This MCP lets you talk to your company’s entire data layer through natural conversation. Instead of navigating menus or building complex reports in a separate application, you just ask your agent what you want to know about your metrics and models. It handles everything from listing available dashboards to retrieving the specific calculation logic for any field. When you connect this MCP through Vinkius, your AI client sees every resource—the workspaces, the underlying data models, and all connected data sources. You can run custom queries against massive datasets right in your chat window and get those results back as a ready-to-use export link in CSV or JSON format. ## Tools ### export_query_results Takes query results and generates a file export link in CSV, JSON, or Excel format. ### get_dashboard_details Retrieves the complete layout and component metadata for a specific BI dashboard. ### get_field_details Fetches detailed information, including calculation logic, for a single data field. ### get_model_details Provides metadata about an entire data model, showing its fields and underlying structure. ### list_data_connections Lists all databases and external sources currently connected to the Omni BI instance. ### list_dashboards Returns a list of all available operational dashboards within the system. ### list_resource_folders Browses and lists organizational folders used to group related BI assets. ### list_data_models Retrieves a list of all defined data models available in the semantic layer. ### list_bi_workspaces Lists all high-level workspaces used to organize and manage different organizational projects. ### run_omni_query Executes a custom, programmatic query against the data models using defined parameters. ## Prompt Examples **Prompt:** ``` List all our sales dashboards. ``` **Response:** ``` Retrieving dashboards... I found 5 related to sales, including 'Global Revenue Overview', 'Quarterly Performance', and 'Sales by Region'. Would you like the component details for the Revenue Overview? ``` **Prompt:** ``` Run a query on the 'Orders' model for fields 'total_price' and 'status'. ``` **Response:** ``` Executing query... I've retrieved the latest 100 records from the Orders model. The data includes prices ranging from $45 to $1,200 across 'shipped' and 'pending' statuses. Shall I generate a CSV export link for the full result set? ``` **Prompt:** ``` What are the field definitions for the 'Customer Retention' model? ``` **Response:** ``` Fetching model details... The 'Customer Retention' model contains 12 fields including 'cohort_month', 'retention_rate' (measure), and 'active_user_count'. Would you like the specific calculation logic for the retention rate? ``` ## Capabilities ### Discover available dashboards List every BI dashboard configured within your organization's instance. ### Inspect data models and fields Examine the structure, metadata, and calculation logic of specific data models and individual fields. ### Run ad-hoc data queries Execute custom queries against your live data models directly through natural language prompts. ### Browse organizational resources List and navigate the available workspaces, folders, and projects within the BI instance. ## Use Cases ### Analyzing Q3 performance metrics A business lead needs to know the regional sales breakdown but doesn't remember which dashboard holds that data. They ask their agent, and it suggests available dashboards using 'list_dashboards', letting them focus on the content instead of the navigation. ### Validating a team member's report A data analyst receives a number from a teammate and needs to know if that field is accurate. They use 'get_field_details' through their agent, instantly retrieving the calculation logic for verification without ever leaving their IDE. ### Preparing for an executive meeting An operations manager must compile quarterly data reports from several sources. Instead of manually querying each system, they ask the agent to run a custom query using 'run_omni_query' and then generate a full export link using 'export_query_results'. ### Mapping out new departmental reporting A project manager needs to know what data sources are available for a new initiative. They use the agent to list all integrated databases via 'list_data_connections' and survey the entire scope of the organization’s BI capabilities. ## Benefits - Stop opening the dashboard UI just to check a metric. You can ask your agent, 'What was the revenue last quarter?' and get an immediate answer without clicking through five different tabs. - Need to know how a number is calculated? Instead of digging into documentation or contacting IT, use the agent to inspect model metadata and see the exact field logic instantly. - Data exports are streamlined. Run your query using 'run_omni_query' and then ask the agent to generate an export link for CSV, JSON, or Excel—all in one chat session. - Keep your work organized by listing resource folders and workspaces directly through conversation. You can browse projects without getting lost in the BI platform’s navigation tree. - When you need to understand data sources, 'list_data_connections' shows you every database Omni is pulling from. It acts like a real-time system inventory for your data team. ## How It Works The bottom line is, you never have to leave your chat window to analyze complex corporate data again. 1. First, subscribe to this MCP and provide your Omni BI Instance URL and API Key (Bearer Token) to Vinkius. 2. Next, you prompt your AI client with a request—like 'Show me the sales dashboards' or 'What fields does the Customer Retention model use?' 3. Finally, the agent executes the necessary queries against your data layer and returns structured results, whether that’s a list of metrics or an export link. ## Frequently Asked Questions **How does Omni BI Intelligence MCP help me run queries?** You tell your agent what query you need and which model it should use. The tool executes the request via 'run_omni_query' against the data layer, giving you immediate results in the chat. **Can I list all my organization’s dashboards with Omni BI Intelligence MCP?** Yes. You simply ask to see a list of available dashboards using 'list_dashboards', which provides an overview of everything your team is tracking. **What is the difference between list_data_models and get_model_details?** Using 'list_data_models' gives you a catalog of all available models. You use 'get_model_details' when you know the model name and need its full metadata, like which fields it contains. **How do I export data from this MCP?** After running any query, simply prompt the agent to generate an export link. The 'export_query_results' tool handles the conversion into CSV, JSON, or Excel files for you. **Does Omni BI Intelligence MCP work with all my data sources?** The agent first uses 'list_data_connections' to show you exactly which databases and external sources are integrated with your specific Omni BI instance, so you know what it can access.