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jwaxman19/qlik-mcp

by Various

An MCP server to run qlik

J

MCP

jwaxman19/qlik-mcp

Added 1 June 2026

Overview

An MCP server that enables AI agents to execute Qlik analytics tasks. It exposes Qlik functionality through the Model Context Protocol, allowing agents to query and interact with Qlik applications programmatically.

Best for

Best for
Developers building AI agents that need to query or control Qlik analytics environments

Use cases

  • Automating Qlik report generation and data extraction
  • Integrating Qlik analytics into AI agent workflows
  • Running Qlik script commands via natural language interfaces

How to use

Tools exposed

  • qlik_get_apps
  • qlik_get_app_sheets
  • qlik_get_sheet_charts
  • qlik_get_chart_data

Tested with

Claude Desktop, Cursor

Example client config

{\n  "mcpServers": {\n    "qlik": {\n      "command": "/path/to/deno",\n      "args": ["run", "--allow-all", "--env-file=.env", "src/index.ts"],\n      "cwd": "/path/to/qlik-mcp"\n    }\n  }\n}

Notes

An MCP server that enables AI agents to execute Qlik analytics tasks. It exposes Qlik functionality through the Model Context Protocol, allowing agents to query and interact with Qlik applications programmatically.

11 stars on GitHub. Last updated 2025-07-27. Licensed MIT.

Use cases

  • Automating Qlik report generation and data extraction
  • Integrating Qlik analytics into AI agent workflows
  • Running Qlik script commands via natural language interfaces

Pros

  • Bridges Qlik analytics with MCP-compatible AI agents
  • Written in TypeScript for type safety and maintainability
  • Lightweight and focused on a single integration task

Cons

  • Low community adoption with only 11 stars
  • Limited documentation and examples available
  • Dependent on Qlik infrastructure and access permissions

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Bridges Qlik analytics with MCP-compatible AI agents
  • Written in TypeScript for type safety and maintainability
  • Lightweight and focused on a single integration task

Cons

  • Low community adoption with only 11 stars
  • Limited documentation and examples available
  • Dependent on Qlik infrastructure and access permissions
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