Qlik MCP

Qlik's MCP server gives AI assistants a governed path into a Qlik Cloud tenant, so an agent works with published analytics instead of querying raw sources. It can list the apps, sheets, spaces and data products a user can reach, describe the fields, dimensions and measures inside an app's data model, and evaluate expressions or run queries whose results come back with the associative model's filtering already applied. Everything goes through Qlik Cloud's own APIs and identity layer, which means space membership, section access and tenant level permissions still decide what an agent can see. That is the point of the integration for regulated teams: the assistant becomes another authenticated client of the same platform, not a side channel around it. Data products and the catalog give an agent a curated set of trusted assets to start from rather than an undifferentiated list of tables. It suits analytics teams, BI developers and data product owners running Qlik Cloud who want conversational access to existing dashboards and models, and developers building agent workflows that need reliable numbers from a governed source. Because it implements standard MCP, it connects to Claude, coding agents and other compatible clients, where an analyst can ask a question in plain language and get an answer traced back to a specific app or data product.