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Qlik Documentation MCP

An offline-first MCP server that gives AI assistants structured access to Qlik Cloud documentation, examples, endpoints, and symbols through local stdio or hosted HTTP transport.

2026 Creator and developer
  • JavaScript
  • TypeScript
  • MCP
  • Qlik Cloud
  • Vercel
  • AI
Qlik Documentation MCP screenshot

Why it exists

Qlik Cloud development often depends on details that are scattered across API references, examples, embedding guides, and product-specific terminology. AI assistants are useful in that workflow, but only when they can ground their answers in the current docs instead of guessing from stale training data.

This project packages Qlik Cloud documentation into an MCP server so AI assistants can search, discover, and retrieve the right source material directly from their client.

Architecture

The system has two main parts: an MCP server and a structured documentation snapshot. The snapshot is packaged data, not a runtime scrape, which makes local usage deterministic and fast.

The server exposes tools for search, symbol lookup, REST endpoint resolution, example retrieval, module explanation, and goal-to-API guidance. It supports local stdio clients and a hosted Vercel path with bearer-token authentication.

Design choices

The important decision is offline-first delivery. The documentation snapshot can be refreshed and reviewed separately, while day-to-day usage stays independent of network availability and upstream site changes.

The hosted mode is intentionally pragmatic: stateless transport for serverless deployment, token auth for private deployments, and restricted validation behavior where shelling out would be unsafe.

Current state

Active. It includes snapshot refresh, a local snapshot browser, validation tooling, and a Vercel-compatible /mcp endpoint for remote clients.