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Overview

WET (Web Extended Toolkit) – Overview

Section titled “WET (Web Extended Toolkit) – Overview”

Web search, content extraction, media discovery, and version-aware library-docs indexing – packaged as one MCP server so an AI agent can research the open web, read pages and local files, and pull framework documentation without leaving the conversation.

What it does

Section titled “What it does”
  • Search the web (metasearch), academic sources, and X/Twitter, plus auto-indexed library documentation with project-scoped version locking.
  • Extract clean content from URLs and local files (PDF/DOCX/PPTX/XLSX to Markdown), with batch, crawl, site-map, structured-extraction, page-interaction, and multi-step research-agent modes.
  • Media: discover and download images, video, and audio from a page.
  • Everything fetched from the open web is wrapped in an XPIA safety marker so the model treats the content as data, not instructions.

Tools

Section titled “Tools”

Three multiplexed capability tools – search, extract, and media, each driven by an action parameter – plus the two universal tools every server in this stack ships: config (status, runtime settings, credential setup) and help (full per-tool docs). In HTTP self-host mode, config__open_relay reopens the browser credential form. Every action and parameter is listed in the tools reference.

Clients

Section titled “Clients”

Runs over stdio with any MCP client – Claude Code, Codex, Gemini CLI, Cursor, and Windsurf. Self-host the HTTP build for claude.ai web compatibility and multi-user, per-user credential isolation. See the modes overview.

Configuration

Section titled “Configuration”

Basic web search works with no credentials. Optional capabilities are unlocked with your own keys and model chains, all supplied as environment variables – leave any unset to fall back to bundled local defaults:

  • EMBEDDING_MODELS, RERANK_MODELS, LLM_MODELS – optional CSV model chains for embedding, reranking, and LLM features; empty falls back to the bundled local model or disables the feature.
  • Provider API keys (JINA_AI_API_KEY, GEMINI_API_KEY, OPENAI_API_KEY, COHERE_API_KEY) and GITHUB_TOKEN for a higher docs-discovery rate limit.

Use placeholders in shared config and never commit real keys. Full walkthrough in setup.

Next steps

Section titled “Next steps”