Context7
Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.
Description from the maker (original English)
Open-source MCP server for AI agents: web search, content extraction, and library docs.
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
OPENROUTER_API_KEY, GITHUB_TOKENValues marked secret are keys to your account. Never share them or paste them into a chat.
You need
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-mcpFill in the empty values before running it.
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.
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.
These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
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
The registry name was verified with the GitHub account n24q02m, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
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.
You need to fill in: OPENROUTER_API_KEY, GITHUB_TOKEN
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).
The GitHub repo last changed –, and the latest version (3.20.0) reached the registry 10 days ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.
In the same category: Context7, Codebase Memory, Exa
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
Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Connect AI agents to Exa for web search, content fetching, and multi-step research.
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.
Distribution & CLI: the repo, CLI and Python module are
wet. The PyPI distribution is `n24q02m-wet` (installpip install n24q02m-wet/uvx n24q02m-wet). wet is an HTTP-only MCP server: start it withwet server startand point clients athttp://127.0.0.1:8000/mcp. There is no stdio mode; a barewetprints the control-plane usage. Thewetandwet-mcpaliases remain available.
mcp-name: io.github.n24q02m/wet
Open-source MCP server for AI agents: web search, content extraction, and library docs.
| 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 | Shipped | 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 (v2.0.0) |
Current release: v3.x.
media(action="analyze")was removed in the
v2.0.0 BREAKING release. Use
understandaction for vision/audio/video analysis. See
docs/migration.mdfor the upgrade recipe.
Sister projects from n24q02m (click to expand)
| Project | Tagline | Tag |
|---|---|---|
| crg | Knowledge graph for token-efficient code reviews -- semantic search and call-... | MCP |
| better-drive | 2-way Google Drive sync with .driveignore filter — rclone engine, Windows tray | Tooling |
| better-email-mcp | IMAP/SMTP email for AI agents -- read, send, organize folders, and manage att... | MCP |
| better-godot-mcp | Composite MCP server for Godot Engine -- 17 composite tools for AI-assisted g... | MCP |
| better-notion-mcp | Markdown-first Notion for AI agents -- pages, databases, blocks, and comments... | MCP |
| better-semantic-release | Drop-in python-semantic-release fork with built-in release-safety guards (orp... | Tooling |
| better-telegram-mcp | Telegram for AI agents -- messages, chats, media, and contacts across both bo... | MCP |
| better-workspace-mcp | Google Workspace MCP server (Docs/Drive/Calendar/Gmail/Sheets/Slides/Tasks/Ch... | MCP |
| claude-plugins | Claude Code plugin marketplace for the n24q02m MCP servers -- install web sea... | Marketplace |
| imagine-mcp | Image and video understanding + generation for AI agents -- across Gemini, Op... | MCP |
| jules-task-archiver | Chrome Extension for bulk operations on Jules tasks via batchexecute API -- a... | Tooling |
| mcp-core | Shared foundation for building MCP servers -- Streamable HTTP transport, OAut... | MCP |
| mnemo | Persistent AI memory with hybrid search and embedded sync. Open, free, unlimi... | MCP |
| fastretrieval | Multi-model embedding and reranking runtime via ONNX and GGUF | Library |
| skret | Secrets without the server. | CLI |
| tacet | A self-distilling neuro-symbolic cascade that amortises LLM cost across knowl... | Tooling |
| web-core | Shared web infrastructure package for search, scraping, HTTP security, and st... | Library |
| wet | Open-source MCP server for AI agents: web search, content extraction, and lib... | MCP |
SEARCH_BACKENDSn24q02m-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 mappinganalyze was removed in v2.0.0 -- use imagine-mcp.understand for vision/audio inference[models.embed|rerank|chat|jev_score] cells in ~/.wet/config.toml (OpenRouter default; one OPENROUTER_API_KEY serves every cell)# Method 1 (default): plugin install via Claude Code
/plugin marketplace add n24q02m/claude-plugins /plugin install wet@n24q02m-plugins
uvx --python 3.13 --from n24q02m-wet wet server start claude mcp add --transport http wet http://127.0.0.1:8000/mcp
docker compose up --build -d
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):
| Client | Install |
|---|---|
| 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 |
| Codex | register the HTTP URL under mcp_servers in ~/.codex/config.toml |
| Gemini CLI | add the mcpServers JSON below to ~/.gemini/settings.json |
| Cursor / Windsurf | add 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).
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.
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.
# 1. Mint a token and its scrypt hash (hull-core canonical; the hash command
openssl rand -hex 32 # the token — give it to clients, keep it secret uv run wet token hash # paste the output as token_hash
cp docker-config/config.example.toml docker-config/config.toml
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.
# 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 " "
claude mcp add --transport http wet http://127.0.0.1:8000/mcp \ --header "Authorization: Beare
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