AnyDocs MCP

Example Use Cases

• 1

  Persistent, on-demand access to any documentation site within their IDE context.

• 2

  Improve reasoning accuracy by embedding compressed documentation indexes.

• 3

  Shift from pre-training-led to retrieval-led reasoning with minimal latency.

Description

AnyDocs MCP enables AI coding agents to access documentation by scraping sites and embedding a compact index directly into the agent's context, improving retrieval-led reasoning. It supports multiple IDEs and agents like Windsurf, Cursor, Claude Code, and Antigravity. The system uses a 7-step LLM-assisted scraping pipeline and stores docs globally for reuse across projects.