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PopNx MCPMCP servers for people who use AI · explained in plain words

Wet

by n24q02mversion 3.20.0i★ –iRuns on your computer
Registry nameio.github.n24q02m/wet

Install

Overview

Description from the maker (original English)

Open-source MCP server for AI agents: web search, content extraction, and library docs.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Search & AI memory
  • You need to fill in: OPENROUTER_API_KEY, GITHUB_TOKEN

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • You fill in yourself: OPENROUTER_API_KEY, GITHUB_TOKEN

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

  • PyPIPython’s uv installed (for the uvx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "wet": {
      "command": "uvx",
      "args": [
        "wet-mcp"
      ],
      "env": {
        "OPENROUTER_API_KEY": "your-value",
        "GITHUB_TOKEN": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add wet --env OPENROUTER_API_KEY=your-value --env GITHUB_TOKEN=your-value -- uvx wet-mcp

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "wet": {
      "command": "uvx",
      "args": [
        "wet-mcp"
      ],
      "env": {
        "OPENROUTER_API_KEY": "your-value",
        "GITHUB_TOKEN": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "wet": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "wet-mcp"
      ],
      "env": {
        "OPENROUTER_API_KEY": "your-value",
        "GITHUB_TOKEN": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

  • OPENROUTER_API_KEY secret env
    OpenRouter API key — the single default credential for the [models.embed|rerank|chat|jev_score] provider cells and the openrouter search backend. Per-task overrides live in ~/.wet/config.toml; keys m…
  • GITHUB_TOKEN secret env
    GitHub personal access token for higher rate limits on library discovery

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account n24q02m, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Search & AI memoryi

  • More stars than 0% of the other 5659 servers in this category
  • Published to the registry more recently than 79% of the other 5659 servers in this category
  • Basic checks equal to or better than 100% of the other 5659 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Wet safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

You need to fill in: OPENROUTER_API_KEY, GITHUB_TOKEN

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (3.20.0) reached the registry 10 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Context7, Codebase Memory, Exa

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Context7

by upstash

Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

Computer or cloud★ 64,224MITUpdated yesterday
Install

Codebase Memory

by DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

Runs on your computer★ 48,148MITUpdated 21 days ago
Install

Exa

by exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

Runs in the cloud★ 5,213MITUpdated 2 months ago
Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

WET - Web Extended Toolkit MCP Server

Distribution & CLI: the repo, CLI and Python module are wet. The PyPI distribution is `n24q02m-wet` (install pip install n24q02m-wet / uvx n24q02m-wet). wet is an HTTP-only MCP server: start it with wet server start and point clients at http://127.0.0.1:8000/mcp. There is no stdio mode; a bare wet prints the control-plane usage. The wet and wet-mcp aliases remain available.

mcp-name: io.github.n24q02m/wet

Open-source MCP server for AI agents: web search, content extraction, and library docs.

PhaseStatusScope
Phase 1Shippedweb-core ScrapingAgent migration, smart chunks output, search polish, media slim
Phase 2ShippedContext7-level docs search: library index (Tier 1 + Tier 2), version-aware queries with token cap, project lock (Cabinets)
Phase 3Shippedextract.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 (v2.0.0)

Current release: v3.x. media(action="analyze") was removed in the

v2.0.0 BREAKING release. Use

imagine-mcp's

understand action for vision/audio/video analysis. See

docs/migration.md for the upgrade recipe.

Sister projects from n24q02m (click to expand)

ProjectTaglineTag
crgKnowledge graph for token-efficient code reviews -- semantic search and call-...MCP
better-drive2-way Google Drive sync with .driveignore filter — rclone engine, Windows trayTooling
better-email-mcpIMAP/SMTP email for AI agents -- read, send, organize folders, and manage att...MCP
better-godot-mcpComposite MCP server for Godot Engine -- 17 composite tools for AI-assisted g...MCP
better-notion-mcpMarkdown-first Notion for AI agents -- pages, databases, blocks, and comments...MCP
better-semantic-releaseDrop-in python-semantic-release fork with built-in release-safety guards (orp...Tooling
better-telegram-mcpTelegram for AI agents -- messages, chats, media, and contacts across both bo...MCP
better-workspace-mcpGoogle Workspace MCP server (Docs/Drive/Calendar/Gmail/Sheets/Slides/Tasks/Ch...MCP
claude-pluginsClaude Code plugin marketplace for the n24q02m MCP servers -- install web sea...Marketplace
imagine-mcpImage and video understanding + generation for AI agents -- across Gemini, Op...MCP
jules-task-archiverChrome Extension for bulk operations on Jules tasks via batchexecute API -- a...Tooling
mcp-coreShared foundation for building MCP servers -- Streamable HTTP transport, OAut...MCP
mnemoPersistent AI memory with hybrid search and embedded sync. Open, free, unlimi...MCP
fastretrievalMulti-model embedding and reranking runtime via ONNX and GGUFLibrary
skretSecrets without the server.CLI
tacetA self-distilling neuro-symbolic cascade that amortises LLM cost across knowl...Tooling
web-coreShared web infrastructure package for search, scraping, HTTP security, and st...Library
wetOpen-source MCP server for AI agents: web search, content extraction, and lib...MCP

Table of contents

  • Features
  • Status
  • Quick install
  • Self-host usage
  • Configuration
  • Documentation
  • Tools
  • CLI
  • 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. Optional cloud search backends (Tavily, Brave, Exa, Kagi, OpenRouter, Firecrawl) as a fallback chain via SEARCH_BACKENDS
  • 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 -> render backends from BROWSER_BACKENDS (native / browserless / cf-browser-rendering) -> optional key-gated captcha), 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 was removed in v2.0.0 -- use imagine-mcp.understand for vision/audio inference
  • Anti-bot -- Stealth strategies bypass Cloudflare, Medium, LinkedIn, Twitter
  • Zero Config -- Built-in local reference embedding + reranking through fastretrieval, no API keys needed. Optional cloud models configured per task via the [models.embed|rerank|chat|jev_score] cells in ~/.wet/config.toml (OpenRouter default; one OPENROUTER_API_KEY serves every cell)

Quick install

# Method 1 (default): plugin install via Claude Code

/plugin marketplace add n24q02m/claude-plugins /plugin install wet@n24q02m-plugins

Method 2 (CLI): start a local instance, then register its HTTP endpoint

uvx --python 3.13 --from n24q02m-wet wet server start claude mcp add --transport http wet http://127.0.0.1:8000/mcp

Method 3 (always-on): compose stack from a clone of this repo (token auth)

docker compose up --build -d

Method 4 (remote): point a client at an HTTP deployment

claude mcp add --transport http wet https:// /mcp

Every method needs a running instance: wet never runs as a client-spawned subprocess. Install matrix (all Streamable HTTP; see the Setup page for full steps):

ClientInstall
Claude Code (plugin)/plugin marketplace add n24q02m/claude-plugins then /plugin install wet@n24q02m-plugins (set WET_URL, default http://127.0.0.1:8000/mcp; optional WET_TOKEN); start the instance first
Claude Code (CLI)claude mcp add --transport http wet http://127.0.0.1:8000/mcp
Codexregister the HTTP URL under mcp_servers in ~/.codex/config.toml
Gemini CLIadd the mcpServers JSON below to ~/.gemini/settings.json
Cursor / Windsurfadd the mcpServers JSON below via the client's MCP settings (mcp.json)
Any client (HTTP self-host)point the client at https:// /mcp (Streamable HTTP, Bearer token when auth = "token" / "multi")

Public OCI image publication is discontinued. Existing historical registry tags remain untouched; new container deployments build from source or use the Cloudflare-managed registry.

The HTTP endpoint speaks Streamable HTTP. With auth = "token" or "multi" the client sends Authorization: Bearer ; no-auth is loopback-only. Stand one up via Method 2 or 3.

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

Self-host usage

Two supported ways to run the always-listening HTTP server. In both, the MCP endpoint is http://127.0.0.1:8000/mcp (Streamable HTTP) and the config root is ~/.wet/ (config.toml, docs.db, subs/). Never run the server as a spawned subprocess of a client — register the endpoint in your client instead.

Dev (uv, no-auth loopback)
git clone https://github.com/n24q02m/wet && cd wet

uv run wet config init # writes ~/.wet/config.toml (default: auth = "no-auth") uv run wet server start # serves http://127.0.0.1:8000/mcp (--foreground to stay attached)

no-auth refuses non-loopback binds — the server is localhost-only until you switch to token auth.

Always-on (docker)
# 1. Mint a token and its scrypt hash (hull-core canonical; the hash command

never echoes the token itself)

openssl rand -hex 32 # the token — give it to clients, keep it secret uv run wet token hash # paste the output as token_hash

2. Instance config from the example

cp docker-config/config.example.toml docker-config/config.toml

edit [server] token_hash and the [models.*] cells (see below)

3. Data continuity (optional): carry an existing instance over by copying

docs.db and subs/ into the wet-home named volume BEFORE first start:

docker volume create wet-wet-home && \ docker cp ~/.wet/docs.db wet-wet-home:/docs.db && \ docker cp ~/.wet/subs wet-wet-home:/subs # adjust: files land as root, chown 999:999

docker compose up -d --build

Compose publishes 127.0.0.1:${WET_PORT:-8000} → container 8000 (loopback only) and mounts docker-config/config.toml read-only at /home/appuser/.wet/config.toml. Persistent data (docs.db, subs/) lives in the wet-home named volume; the download/cache dir in wet-data. Editing the config takes effect on docker compose restart.

Consumers
# CLI (talks to the running server over HTTP; exits 2 with a hint when none runs):

uvx --python 3.13 --from n24q02m-wet wet search " "

MCP client (Claude Code):

claude mcp add --transport http wet http://127.0.0.1:8000/mcp \ --header "Authorization: Beare

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