Overview
What is Qlik Sense MCP Server?
Qlik Sense MCP Server integrates Qlik Sense Enterprise with systems supporting the Model Context Protocol (MCP), providing a unified interface for Repository API and Engine API operations. It offers 21 tools for managing applications, data, users, and analytics.
How to use Qlik Sense MCP Server?
Install via uvx qlik-sense-mcp-server (recommended) or pip install qlik-sense-mcp-server. Configure environment variables for server URL, user directory, certificate paths, and API ports in a .env file. Start the server with uvx qlik-sense-mcp-server or qlik-sense-mcp-server. Then call any of the 21 tools through your MCP client.
Key features of Qlik Sense MCP Server
- Unified API for all Qlik Sense REST and WebSocket APIs
- Certificate‑based authentication for secure access
- Optimized queries and response handling
- Multiple data export formats (JSON, CSV, simple)
- Advanced analytics via hypercube creation
Use cases of Qlik Sense MCP Server
- Retrieve lists of applications, users, streams, tasks, and data connections
- Open apps and extract load scripts, fields, sheets, and table data
- Perform field‑value analysis with frequency and statistics
- Create hypercubes for custom multi‑dimensional analytics
- Export application data in various formats for downstream tools
FAQ from Qlik Sense MCP Server
What exactly does the MCP server do?
It bridges Qlik Sense Enterprise with Model Context Protocol, exposing Repository API and Engine API operations as MCP tools so any MCP‑compatible client can interact with Qlik Sense.
How do I install it?
Recommended: run uvx qlik-sense-mcp-server. Alternatively, install from PyPI with pip install qlik-sense-mcp-server or clone the repository and run make dev.
What API operations are supported?
Ten Repository API commands (e.g., get_apps, get_users, start_task) and eleven Engine API commands (e.g., engine_open_app, engine_get_script, engine_create_hypercube, engine_create_data_export).
How do I configure the server for my Qlik Sense instance?
Create a .env file with QLIK_SERVER_URL, QLIK_USER_DIRECTORY, QLIK_USER_ID, certificate paths (QLIK_CLIENT_CERT_PATH, etc.), and API ports. Then start the server with those variables set.
What are the system requirements?
Python 3.12 or later, a Qlik Sense Enterprise server, valid certificates for authentication, and network access to the Qlik Sense server.
