Qlik Documentation MCP
An offline-first server that gives AI assistants structured access to documentation, examples, endpoints, and symbols through local stdio or hosted HTTP transport.
Why it exists
Cloud development often depends on details that are scattered across references, examples, 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, endpoint resolution, example retrieval, module explanation, and goal-to-API guidance. It supports local stdio clients and a hosted path with bearer- authentication.
Offline first
Offline-first delivery is the decision everything else follows from. The snapshot gets refreshed and reviewed as its own step, which means a Qlik docs-site redesign cannot break anybody's editor on a Tuesday afternoon.
The hosted makes the compromises a deployment forces: stateless transport, token auth for private deployments, and validation that refuses to shell out where doing so 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.