# Sigma Computing MCP for AI Agents AI Agent Connect > Sigma Computing MCP lets your AI agent navigate your BI environment. It pulls workbook lists, maps out data connections, and audits team structures without you having to click through the web UI. It's designed for teams who need to see their data landscape clearly. ## Overview - **Category:** data-analytics - **Price:** Free - **Endpoint:** https://edge.vinkius.com/vk_preview_gQm7h5oIY5gOVePr0VgifFP0jBzhq0ebXuCRDTAj/ai-agent-connect - **Tags:** data-lineage, workbook-management, cloud-bi, data-stewardship, analytical-metadata, database-integration ## Description Sigma Computing MCP gives your AI agent a direct line into your organization's data analytics metadata. Instead of hunting through heavy browser tabs to find which workbooks belong to a specific department or figuring out which datasets power a dashboard, you can just ask your agent. It acts like a data steward that knows where everything lives. You can see the connections between your Snowflake or BigQuery sources and the final reports they feed into. It's a huge time saver when you're trying to map out data lineage or find out who owns a specific set of analytics. If you're looking for a way to make your BI environment more searchable, this is how you do it. It fits right into your workflow on Vinkius, making it easy to keep your data governance on track. You can get a full inventory of workbooks or see every team in your organization with a single prompt. This takes the manual work out of auditing your BI stack. ## Tools ### list_workbooks Lists all workbooks in the Sigma organization. This helps you see every available report at once. ### get_workbook_details Retrieves details for a specific workbook. Use this to see the metadata of a single report. ### list_workbook_pages Lists all pages within a specific workbook. This shows you the layout of a specific report. ### list_connections Lists data source connections configured in Sigma. Use this to see what databases are linked. ### list_organization_members Lists all users in the Sigma organization. This gives you a full view of your user base. ### list_organization_teams Lists all teams in the Sigma organization. This helps you see how the company is structured. ### list_datasets Lists all datasets available in the organization. Use this to find the raw data building blocks. ## Prompt Examples **Prompt:** ``` Show me all the workbooks we have for the sales team. ``` **Response:** ``` ### Sales Team Workbooks I found the following workbooks associated with the sales department: | Workbook Name | Workbook ID | | :--- | :--- | | Q3 Sales Performance | `wb_9921` | | Regional Revenue Map | `wb_8832` | | Lead Conversion Tracker | `wb_7741` | Would you like to see the specific pages for any of these? ``` **Prompt:** ``` Who are the members of our data engineering team? ``` **Response:** ``` ### Data Engineering Team The following members are currently assigned to the **Data Engineering** team: * Alex Rivera * Jordan Smith * Casey Chen * Morgan Lee There are **4** members total in this group. ``` **Prompt:** ``` What datasets are currently available in our organization? ``` **Response:** ``` ### Available Datasets I've pulled the full list of datasets available in your Sigma organization: * **Marketing_Leads_Master** * **Finance_Quarterly_Actuals** * **Product_Inventory_Sync** * **User_Engagement_Metrics** * **Churn_Risk_Score_v2** Let me know if you'd like to see which workbooks depend on a specific one. ``` ## Capabilities ### List all workbooks Get a full inventory of every workbook in your Sigma organization. ### Audit data connections See every backend data source connection configured in the platform. ### Map dataset lineage Identify which datasets are available across your entire organization. ### Track team structures See every team and member within your Sigma organization. ### Drill into workbook pages View the specific pages contained within a single workbook. ### Inspect workbook details Pull specific metadata for a single workbook. ## Use Cases ### Audit Data Lineage A data engineer needs to see where a specific report gets its data. They ask the agent to list all datasets and connections to find the source. ### Team Onboarding A manager wants to know who is in the Marketing team. The agent uses list_organization_teams and list_organization_members to provide a list. ### Report Discovery An analyst wants to see if a North America report already exists. They use list_workbooks to check the current inventory. ### Metadata Extraction A developer needs to know how many pages are in a specific workbook. They use list_workbook_pages to get the count. ## Benefits - Stop hunting for reports. Use list_workbooks to get a complete inventory of every workbook in seconds. - Audit your data sources quickly. list_connections lets you see every backend pipe without digging into settings. - Map your data lineage easily. Use list_datasets to see the building blocks of your entire analytics stack. - Manage your team topology. list_organization_teams and list_organization_members give you a bird's eye view of your users. - Save time on report audits. Use get_workbook_details and list_workbook_pages to see report content instantly. ## How It Works The bottom line is you get instant visibility into your BI metadata without opening a browser. 1. Add your SIGMA_CLIENT_ID and SIGMA_CLIENT_SECRET to your environment variables. 2. Connect the Sigma Computing MCP through the Vinkius catalog to your agent. 3. Ask your agent to find specific workbooks, teams, or data connections. ## Frequently Asked Questions **Can the Sigma Computing MCP help me find specific reports?** Yes, it lists all workbooks so you can see what's already built. This helps you identify existing reports quickly without browsing every dashboard manually. **How do I see what databases are connected to Sigma?** You can ask the agent to list all your data source connections. This provides a clear view of every backend pipe linked to your BI platform. **Can I use this to see who is in my organization?** Yes, it lists all members and teams within your Sigma account. This is great for getting a bird's eye view of your user base and team structures. **Does the Sigma Computing MCP show me the actual data in my tables?** No, it only shows metadata like workbooks and datasets. It's designed for exploring the structure of your BI environment rather than querying individual rows. **Can I use this to map out our data lineage?** Yes, it helps you see the connection between sources, datasets, and reports. You can use it to audit how data flows from your backend into your final dashboards. **How does this help with data governance?** It helps with governance by providing a fast way to audit your entire BI environment. You can quickly verify which teams have access and what datasets are being used. **Can the integration forcefully modify datasets or override workbook queries directly?** No. By structured intent, this module is strictly bounded as an observational and auditing matrix targeting specifically organizational discovery heavily optimized securely natively. Explicit write protocols structurally enabling queries, mutation mappings, or data modifications systematically inherently simply completely systematically bypassed unconditionally directly universally. **Why construct this manually over leveraging the standard platform web UI interfaces?** The native IDE integration context decisively grants explicitly your agent prompt active unadulterated runtime authority seamlessly querying real-time underlying arrays dynamically without latency immediately directly mapping structurally uniquely native taxonomies avoiding graphical interface lags flawlessly intrinsically seamlessly definitively completely. **Does my client credentials require explicit specific elevated Admin privileges exclusively natively?** Yes explicitly securely seamlessly thoroughly definitively successfully extensively confidently conclusively exactly absolutely entirely solidly reliably exactly correctly perfectly. 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