How do I install Wet?

Wet is a local plugin. Install it using PyPI package: wet-mcp and add the generated configuration snippet to your AI app's MCP config file. Then restart your AI app.

What credentials does Wet need?

Wet requires the following credentials or environment variables: API_KEYS, GITHUB_TOKEN. You can find setup instructions on the server detail page.

What AI apps work with Wet?

Wet uses the Model Context Protocol (MCP) and works with any MCP-compatible AI app, including Claude, ChatGPT / Codex, Gemini, Copilot, Cursor, and more.

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Wet MCP Server

by N24q02m

Search & WebLow Risk10.0MCP RegistryLocal

Free

Server data from the Official MCP Registry

MCP server for web search, content extraction, academic research, and library docs.

About

MCP server for web search, content extraction, academic research, and library docs.

Security Report

10.0

Low Risk10.0Low Risk

Valid MCP server (1 strong, 1 medium validity signals). No known CVEs in dependencies. Package registry verified. Imported from the Official MCP Registry. Trust signals: trusted author (17/17 approved).

4 files analyzed · 1 issue found

Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.

Permissions Required

This plugin requests these system permissions. Most are normal for its category.

env_vars

Check that this permission is expected for this type of plugin.

What You'll Need

Set these up before or after installing:

API keys for cloud embedding and media analysis (format: ENV_VAR:key). Example: GOOGLE_API_KEY:AIza...Required

Environment variable: API_KEYS

GitHub personal access token for higher rate limits on library discoveryRequired

Environment variable: GITHUB_TOKEN

How to Install

Add this to your MCP configuration file:

{
  "mcpServers": {
    "io-github-n24q02m-wet-mcp": {
      "env": {
        "API_KEYS": "your-api-keys-here",
        "GITHUB_TOKEN": "your-github-token-here"
      },
      "args": [
        "wet-mcp"
      ],
      "command": "uvx"
    }
  }
}

Documentation

View on GitHub

From the project's GitHub README.

WET - Web Extended Toolkit MCP Server

mcp-name: io.github.n24q02m/wet-mcp

Open-source MCP Server for web search, content extraction, library docs & multimodal analysis.

Features

Web Search -- Embedded SearXNG metasearch (Google, Bing, DuckDuckGo, Brave) with filters, semantic reranking, query expansion, and snippet enrichment
Academic Research -- Search Google Scholar, Semantic Scholar, arXiv, PubMed, CrossRef, BASE
Library Docs -- Auto-discover and index documentation with FTS5 hybrid search, HyDE-enhanced retrieval, and version-specific docs
Content Extract -- Clean content extraction (Markdown/Text), structured data extraction (LLM + JSON Schema), batch processing (up to 50 URLs), deep crawling, site mapping
Local File Conversion -- Convert PDF, DOCX, XLSX, CSV, HTML, EPUB, PPTX to Markdown
Media -- List, download, and analyze images, videos, audio files
Anti-bot -- Stealth mode bypasses Cloudflare, Medium, LinkedIn, Twitter
Zero Config -- Built-in local Qwen3 embedding + reranking, no API keys needed. Optional cloud providers (Jina AI, Gemini, OpenAI, Cohere)
Sync -- Cross-machine sync of indexed docs via Google Drive (OAuth Device Code, no browser redirect)

Setup

With AI Agent -- copy and send this to your AI agent:

Please set up wet-mcp for me. Follow this guide: https://raw.githubusercontent.com/n24q02m/wet-mcp/main/docs/setup-with-agent.md

Manual Setup -- follow docs/setup-manual.md

Tools

Tool	Actions	Description
`search`	`search`, `research`, `docs`, `similar`	Web search (with filters, reranking, expand/enrich), academic research, library docs (HyDE), find similar
`extract`	`extract`, `batch`, `crawl`, `map`, `convert`, `extract_structured`	Content extraction, batch processing (up to 50 URLs), deep crawling, site mapping, local file conversion, structured data extraction (JSON Schema)
`media`	`list`, `download`, `analyze`	Media discovery, download, and analysis
`config`	`status`, `set`, `cache_clear`, `docs_reindex`	Server configuration and cache management
`setup`	`open_relay`, `status`, `skip`, `reset`, `complete`, `warmup`, `setup_sync`	Credential setup (browser relay, local-only mode, reset), status check, model warmup, Google Drive sync
`help`	--	Full documentation for any tool

Security

SSRF prevention -- URL validation on crawl targets
Graceful fallbacks -- Cloud → Local embedding, multi-tier crawling
Error sanitization -- No credentials in error messages
File conversion sandboxing -- Optional CONVERT_ALLOWED_DIRS restriction

Build from Source

git clone https://github.com/n24q02m/wet-mcp.git
cd wet-mcp
uv sync
uv run wet-mcp

License

MIT -- See LICENSE.

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