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 (11/11 approved).

9 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

5-strategy web search + extract + media MCP server, web-core ScrapingAgent backend.

Phase	Status	Scope
Phase 1	Shipped	web-core ScrapingAgent migration, smart chunks output, search polish, media slim
Phase 2	Shipped	Context7-level docs search: library index (Tier 1 + Tier 2), version-aware queries with token cap, project lock (Cabinets)
Phase 3	Current (BREAKING v2.0.0)	`extract.agent` multi-step research with cited synthesis, `extract.interact` click/fill/submit via patchright (optional session persistence), `docs_004_chunk_summaries` migration, `media.analyze` removed

BREAKING in v2.0.0 -- media(action="analyze") was removed entirely. Use imagine-mcp's understand action for vision/audio/video analysis. See docs/migration.md for the upgrade recipe.

Project	Tagline	Tag
better-code-review-graph	Knowledge graph for token-efficient code reviews -- fixed search, configurabl...	MCP
better-email-mcp	IMAP/SMTP email server for AI agents -- 6 composite tools with multi-account ...	MCP
better-godot-mcp	Composite MCP server for Godot Engine -- 17 mega-tools for AI-assisted game d...	MCP
better-notion-mcp	Markdown-first Notion API server for AI agents -- 10 composite tools replacin...	MCP
better-telegram-mcp	MCP server for Telegram with dual-mode support: Bot API (httpx) for quick bot...	MCP
claude-plugins	Full documentation: mcp.n24q02m.com — unified docs for all 8 servers + the mc...	Marketplace
imagine-mcp	Production-grade MCP server for image and video understanding + generation ac...	MCP
jules-task-archiver	Chrome Extension for bulk operations on Jules tasks via batchexecute API -- a...	Tooling
mcp-core	Unified MCP Streamable HTTP 2025-11-25 transport, OAuth 2.1 Authorization Ser...	MCP
mnemo-mcp	Persistent AI memory with hybrid search and embedded sync. Open, free, unlimi...	MCP
qwen3-embed	Lightweight Qwen3 text embedding and reranking via ONNX Runtime and GGUF	Library
skret	Secrets without the server.	CLI
web-core	Shared web infrastructure package for search, scraping, HTTP security, and st...	Library
wet-mcp	Open-source MCP Server for web search, content extraction, library docs & mul...	MCP

Features
Status
Quick install
Documentation
Tools
Comparison
Security
Build from Source
Trust Model
License

Features

Web Search -- Embedded SearXNG metasearch (Google, Bing, DuckDuckGo, Brave) with query expansion, TTL cache (1 h general / 5 min time-sensitive), standardized citation format, and 200-token snippet cap
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 -- 5-strategy escalation chain via n24q02m-web-core ScrapingAgent (basic_http -> tls_spoof -> headless Crawl4AI), markitdown bridge for low-tier HTML/MD fallback, smart chunks structured output (clean text + markdown + JSON-LD + code blocks + metadata), 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 images / videos / audio files. analyze deprecated v<auto>+ -- use imagine-mcp.understand for vision/audio inference
Anti-bot -- Stealth strategies bypass Cloudflare, Medium, LinkedIn, Twitter
Zero Config -- Built-in local Qwen3 embedding + reranking, no API keys needed. Optional cloud providers (Jina AI, Gemini, OpenAI, Cohere) for higher-quality vectors
Sync -- Cross-machine sync of indexed docs via Google Drive (OAuth Device Code, no browser redirect)

Quick install

# Method 1 (default): plugin install via Claude Code
/plugin marketplace add n24q02m/claude-plugins
/plugin install wet-mcp@n24q02m-plugins

# Method 1 (CLI): direct uvx invocation
claude mcp add wet -- uvx wet-mcp

# Method 3 (recommended for HTTP / multi-device / OAuth)
docker run -d --name wet-mcp-http -p 8084:8080 \
  -v wet-data:/data -e MCP_TRANSPORT=http \
  -e PUBLIC_URL=https://wet.example.com \
  n24q02m/wet-mcp:latest

Full setup matrices live at the canonical docs site mcp.n24q02m.com/servers/wet-mcp/setup/ and the paste-to-agent snippets at claude-plugins/plugins/wet-mcp/setup-with-agent.md (per Spec F single source of truth).

Status

2026-05-02 -- Architecture stabilization update

Past months saw significant churn around credential handling and the daemon-bridge auto-spawn pattern. This caused multi-process races, browser tab spam, and inconsistent setup UX across plugins. As of v<auto>, the architecture is stable: 2 clean modes (stdio + HTTP), no daemon-bridge layer, no auto-spawn from stdio.

Apologies for the instability period. If you encountered issues with prior versions, please update to v<auto>+ and follow the current setup docs -- most prior workarounds are no longer needed.

Related plugins from the same author:

wet-mcp -- Web search + content extraction

mnemo-mcp -- Persistent AI memory

imagine-mcp -- Image/video understanding + generation

better-notion-mcp -- Notion API

better-email-mcp -- Email management

better-telegram-mcp -- Telegram

better-godot-mcp -- Godot Engine

better-code-review-graph -- Code review knowledge graph

All plugins share the same architecture (this spec) -- install once, learn pattern transfers.

Documentation

Full docs at mcp.n24q02m.com/servers/wet-mcp/:

Setup -- install methods for Claude Code, Codex, Gemini CLI, Cursor, Windsurf, mcp.json
Modes overview -- stdio / local-relay / remote-relay / remote-oauth
Multi-user setup -- per-JWT-sub credential model

In-repo references (Spec F single source of truth: setup docs live in claude-plugins/plugins/wet-mcp/):

docs/ARCHITECTURE.md -- web-core ScrapingAgent integration, strategy chain, storage layout, LLM provider dispatch
docs/BENCHMARKS.md -- v1.x baseline coverage / latency placeholders + tier-1 fixture metrics

Install with AI agent -- paste this to your AI coding agent:

Install MCP server wet-mcp following the steps at https://raw.githubusercontent.com/n24q02m/claude-plugins/main/plugins/wet-mcp/setup-with-agent.md

Tools

5 MCP tools (3 domain + config + help). The legacy setup tool merged into config action dispatch.

Tool	Description
`search`	Web (SearXNG metasearch), news, images, academic research (Scholar / arXiv / PubMed / CrossRef / Semantic Scholar / BASE), library docs (HyDE + FTS5), find similar pages. Includes `docs_resolve` (library name -> ranked id), `docs_query` (version-aware + topic + 5000-token cap), `docs_lock_project` (Cabinets project pin via pyproject / package.json / go.mod / Cargo.toml manifest detection).
`extract`	URL -> smart chunks dict (`clean_text` + `markdown` + `structured_data` + `code_blocks` + `metadata`) via web-core 5-strategy chain. Batch processing (up to 50 URLs), deep crawling, site mapping, local file conversion (PDF/DOCX/XLSX/PPTX/EPUB), structured extraction (JSON Schema)
`media`	`list` (discover URLs from gallery pages), `download` (SSRF-safe). `analyze` deprecated v<auto>+ -- forwards to `imagine-mcp.understand`
`config`	`status`, `set`, `cache_clear`, `docs_reindex`, `warmup`, `setup_sync`, `setup_status`, `setup_skip`, `setup_reset`, `setup_complete`
`help`	Per-tool documentation: `search`, `extract`, `media`, `config`

Media boundary: For vision / audio understanding (image captioning, OCR, audio transcription, video summarization), use imagine-mcp. media.analyze was removed in wet v2.0.0 -- use imagine-mcp.understand instead.

Comparison

How wet-mcp stacks up against direct competitors in each pillar:

Capability	wet-mcp	Brave Search	Tavily	Firecrawl	Context7
Web search	Yes (SearXNG aggregation)	Yes	Yes	No	No
Extract URL	Yes (5-strategy chain)	No	Yes (basic)	Yes	No
Media list / download	Yes	No	No	No	No
Library docs search	Yes (Tier 1 curated + Tier 2 on-demand, version-aware, Cabinets)	No	No	No	Yes
Academic research	Yes (6 providers)	No	No	No	No
Self-hostable	Yes	No	No	No	Yes
Free tier	Yes (open source)	Limited	Limited	Limited	Yes

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

Trust Model

This plugin implements TC-Local (machine-bound, single trust principal). See mcp-core/docs/TRUST-MODEL.md for full classification.

Mode	Storage	Encryption	Who can read your data?
stdio (default)	`~/.wet-mcp/config.json`	AES-GCM, machine-bound key	Only your OS user (file perm 0600)
HTTP self-host	Same as stdio	Same	Only you (admin = user)

License

MIT -- See LICENSE.

Reviews

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Wet MCP Server

About

Security Report

Findings (1)

Permissions Required

What You'll Need

How to Install

Documentation

WET - Web Extended Toolkit MCP Server

Table of contents

Features

Quick install

Status

Documentation

Tools

Comparison

Security

Build from Source

Trust Model

License

Reviews

No reviews yet

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mcp-creator-python

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