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Setup with agent

WET (Web Extended Toolkit) – Agent Setup Guide

Section titled “WET (Web Extended Toolkit) – Agent Setup Guide”

2026-08-30 Update: Plugin install (Option 1) uses stdio mode. It provides local Fastretrieval embedding/reranking, extraction, and library docs without API keys. Web search needs a configured cloud/SearXNG endpoint or the locally built Docker image that bundles SearXNG. The previous “Zero-Config Relay” auto-spawn pattern has been removed.

Give this file to your AI agent to automatically set up wet-mcp.

This plugin supports 3 install methods. Pick the one that matches your use case:

Priority Method Transport Best for
1. Default Plugin install (uvx/npx) stdio Quick local start, single workstation, no OAuth/HTTP needed.
2. Fallback Docker stdio (docker run -i --rm) stdio Windows/macOS where native uvx/npx hits PATH or Python version issues.
3. Recommended Docker HTTP (docker run -p 8080:8080) HTTP Multi-device, OAuth/relay-form auth, team self-host, claude.ai web compatibility.

All MCP servers across this stack share this priority hierarchy. better-godot-mcp and better-code-review-graph default to stdio plugin install and do not provide an owner-hosted relay/OAuth endpoint; Docker stdio and operator self-hosted HTTP remain available as advanced paths.

⚠️ Mutually exclusive — pick ONE per plugin: If you choose Method 2 (Docker stdio override) OR Method 3 (HTTP), do NOT also /plugin install this plugin via marketplace. Both load simultaneously and create duplicate entries in /mcp dialog (plugin’s stdio + your override). Plugin matching is by endpoint (URL or command string) per CC docs, not by name — and npx/uvxdocker ≠ HTTP URL, so all three are distinct endpoints. Trade-off: choosing Method 2 or Method 3 means you lose this plugin’s skills/agents/hooks/commands. For full plugin features, use Method 1 (default plugin install) with userConfig credentials prompted at install time.

Option 1: Claude Code Plugin (stdio default)

Section titled “Option 1: Claude Code Plugin (stdio default)”

Plugin install uses stdio mode. Fastretrieval’s local model registry provides ONNX embedding and reranking without API keys; content extraction and library docs also work without a search provider. Web search requires a configured cloud/SearXNG endpoint or the locally built Docker image that bundles SearXNG.

When you run /plugin install, Claude Code prompts you for the following credentials (declared in userConfig per CC docs). Sensitive values are stored in your system keychain and persist across /plugin update:

Field Required Where to obtain
RERANK_MODELS Optional CSV rerank model chain such as jina_ai/jina-reranker-v3; leave empty for Fastretrieval’s local ONNX reranker manifest
JINA_AI_API_KEY Optional https://jina.ai/api-key (highest priority embedding+reranking)
GEMINI_API_KEY Optional https://aistudio.google.com/apikey
OPENAI_API_KEY Optional https://platform.openai.com/api-keys
COHERE_API_KEY Optional https://dashboard.cohere.com/api-keys
GITHUB_TOKEN Optional https://github.com/settings/tokens (bumps GitHub rate limit 60->5000/hr for library docs discovery)
Terminal window
# Install from marketplace (includes skills: /fact-check, /compare)
/plugin marketplace add n24q02m/claude-plugins
/plugin install wet-mcp@n24q02m-plugins

Other optional env vars (EMBEDDING_MODELS, LLM_MODELS, SEARCH_BACKENDS, TAVILY_API_KEY, BRAVE_API_KEY, EXA_API_KEY, BROWSER_BACKENDS, SYNC_ENABLED, etc.) are not part of the userConfig prompt; add them manually to mcpServers.wet.env in your settings if needed.

Without env vars: content extraction, library docs, and Fastretrieval-managed local embedding/reranking work. For web search, configure a cloud/SearXNG backend or use the locally built Docker image; other env vars enable cloud embedding/reranking, LLM analysis, and premium providers.

Note: This installs the full plugin (skills + agents + hooks + commands + stdio MCP server). If you’d rather use Option 2 (Docker stdio) or Option 3 (HTTP) below, DO NOT /plugin install this plugin — pick Option 2 or Option 3 instead. All three methods are mutually exclusive (see Method overview).

⚠️ Before adding the Docker stdio override below, ensure this plugin is NOT installed via marketplace: Run /plugin uninstall wet-mcp@n24q02m-plugins first if you previously ran /plugin install. Otherwise both entries (plugin’s npx/uvx stdio + your docker run stdio) will load simultaneously since plugin matches by endpoint (command string), not by name.

Trade-off accepted: Choosing this method means you lose this plugin’s skills/agents/hooks/commands. Use Option 1 instead if you want full plugin features.

Public OCI publication is discontinued. Clone a release tag, build the stdio target locally, then run it:

Terminal window
git clone --branch <release-tag> --depth 1 https://github.com/n24q02m/wet-mcp.git
cd wet-mcp
docker build --target stdio -t wet-mcp:local .
docker run -i --rm \
--name mcp-wet \
-v wet-data:/data \
-e JINA_AI_API_KEY \
-e GEMINI_API_KEY \
-e OPENAI_API_KEY \
-e COHERE_API_KEY \
-e RERANK_MODELS \
-e BRAVE_API_KEY \
-e TAVILY_API_KEY \
-e EXA_API_KEY \
-e BROWSER_BACKENDS \
-e GITHUB_TOKEN \
wet-mcp:local

Or as an MCP server config:

{
"mcpServers": {
"wet": {
"command": "docker",
"args": [
"run", "-i", "--rm",
"--name", "mcp-wet",
"-v", "wet-data:/data",
"-e", "JINA_AI_API_KEY",
"-e", "GEMINI_API_KEY",
"-e", "GITHUB_TOKEN",
"wet-mcp:local"
]
}
}
}

Stdio mode is the default and works for most personal/single-user scenarios. Consider switching to HTTP mode (Option 3) when you need:

  • claude.ai web compatibility – HTTP transport is required to connect plugins to claude.ai web client (stdio only works with desktop clients)
  • One server shared across N Claude Code sessions – single daemon serves all sessions instead of spawning a fresh stdio process per session (lower memory, shared cache)
  • Browser-based GDrive OAuth flow – HTTP mode performs the Google Device Code flow via the bundled public client; no manual GOOGLE_DRIVE_CLIENT_ID setup required
  • Multi-device credential sync – self-host the HTTP server once, log in from multiple machines without re-pasting API keys
  • Multi-user team sharing – single self-hosted instance supports N users with per-JWT-sub credential isolation
  • Always-on persistent process – ideal for webhooks, scheduled agents, or background automation

⚠️ Before adding the HTTP override below, ensure this plugin is NOT installed via marketplace: Run /plugin uninstall wet-mcp@n24q02m-plugins first if you previously ran /plugin install. Otherwise both entries (plugin’s stdio + your HTTP override) will load simultaneously since plugin matches by endpoint, not name.

Trade-off accepted: Choosing this method means you lose this plugin’s skills/agents/hooks/commands. For example, the wet-mcp:fact-check skill will no longer be available. Use Option 1 instead if you want full plugin features.

Switching transport vs. setting credentials: The userConfig prompt only configures credentials for stdio mode (Method 1 / Option 1). To switch transport to HTTP, override mcpServers in your client settings per the snippets below – this is a separate path from userConfig and is not driven by the install prompt.

HTTP mode runs as a persistent multi-user server with browser-based credential setup. GDrive OAuth uses a bundled public Google Desktop client (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) per Google’s official Desktop OAuth pattern – no user-side OAuth registration is required. Users authenticate via the device-code flow in their browser.

From the wet-mcp checkout, build the HTTP target and run it:

Terminal window
docker build --target http -t wet-mcp-http:local .
docker run -d --name wet-mcp-http \
-p 8080:8080 \
-v wet-data:/data \
-e MCP_TRANSPORT=http \
-e PUBLIC_URL=https://wet.example.com \
-e MCP_DCR_SERVER_SECRET=your-random-secret \
wet-mcp-http:local

Configure MCP client to connect:

{
"mcpServers": {
"wet": {
"url": "https://wet.example.com/mcp"
}
}
}

On first call, the client redirects to the relay form. Fill in API keys (all optional) and – if SYNC_ENABLED=true – complete the GDrive device-code flow in your browser using the bundled public client. Each user receives an isolated credential vault keyed by JWT sub.

Public HTTP deployments expose <your-domain>/authorize to URL discovery. To prevent random Internet users from accessing the relay form, mint a relay password:

Terminal window
openssl rand -hex 32
# Save in your skret / .env as:
MCP_RELAY_PASSWORD=<generated-32-byte-hex>

Share this password out-of-band (Signal/email/SMS) with anyone you invite to use your server. They will see a login form when first opening /authorize; once logged in, the cookie persists 24 hours.

Single-user dev exception: If PUBLIC_URL=http://localhost:8080, you can leave MCP_RELAY_PASSWORD empty to disable the gate. The server logs a warning if you skip the password with a non-localhost PUBLIC_URL.

All environment variables are optional. The server works in local mode (Fastretrieval-managed ONNX embedding + SearXNG) with zero configuration.

Variable Required Default Description
JINA_AI_API_KEY No Jina AI key: search + extraction + embedding + reranking (highest priority)
GEMINI_API_KEY No Google Gemini key: LLM (structured extraction, media analysis) + embedding
GOOGLE_VERTEX_EXPRESS_API_KEY No Vertex AI Express: Gemini via API key, no Service Account. Get it at https://cloud.google.com/vertex-ai/generative-ai/docs/start/express-mode/overview
OPENAI_API_KEY No OpenAI key: LLM + embedding (lower priority than Gemini)
COHERE_API_KEY No Cohere key: embedding + reranking
BRAVE_API_KEY No Brave Search API key (premium search provider)
TAVILY_API_KEY No Tavily Search API key
EXA_API_KEY No Exa Search API key
GITHUB_TOKEN No auto-detect GitHub token for docs discovery (60 -> 5000 req/hr). Auto-detected from gh auth token
Variable Required Default Description
EMBEDDING_MODELS No empty Ordered CSV embedding model chain (provider/model,...); empty resolves Fastretrieval’s local ONNX model manifest
RERANK_MODELS No empty Ordered CSV rerank model chain (provider/model,...); empty resolves Fastretrieval’s local ONNX cross-encoder manifest
EMBEDDING_DIMS No 0 (auto) Embedding dimensions; custom local models may require LOCAL_EMBEDDING_DIM
LOCAL_EMBEDDING_MODEL No Optional BYO local embedding model ID; empty uses Fastretrieval’s bundled model manifest
LOCAL_EMBEDDING_DIM No 0 Required for a BYO local embedding when its model manifest does not provide dimensions
LOCAL_EMBEDDING_POOLING No MEAN Pooling for a BYO local embedding (MEAN, CLS, LAST_TOKEN, or DISABLED)
LOCAL_EMBEDDING_NORMALIZE No true Normalize BYO local embedding outputs
LOCAL_RERANK_MODEL No Optional BYO local reranker model ID; empty uses Fastretrieval’s bundled model manifest
LOCAL_RERANK_MODEL_FILE No onnx/model.onnx ONNX file path for a BYO local reranker
RERANK_ENABLED No true Enable reranking after search
RERANK_TOP_N No 10 Return top N results after reranking
Variable Required Default Description
LLM_MODELS No empty Ordered CSV LLM model chain (provider/model,...); empty leaves optional LLM features disabled

EMBEDDING_BACKEND, EMBEDDING_MODEL, RERANK_BACKEND, and RERANK_MODEL are deprecated and honored for one release. Use the plural EMBEDDING_MODELS and RERANK_MODELS chains instead.

Variable Required Default Description
SEARCH_BACKENDS No searxng Ordered CSV search chain: searxng, tavily, brave, exa
WET_AUTO_SEARXNG No true Auto-start bundled SearXNG when the runtime includes its prerequisites; uvx plugin environments do not bundle them
DISABLE_LOCAL_SEARCH No false Skip the embedded local SearXNG fallback while retaining external or cloud search backends
WET_SEARXNG_PORT No 41592 SearXNG port
SEARXNG_URL No http://localhost:41592 URL for an external SearXNG deployment
SEARXNG_TIMEOUT No 30 SearXNG request timeout in seconds
Variable Required Default Description
BROWSER_BACKENDS No empty -> native Ordered CSV render chain: native, browserless, cf-browser-rendering
DISABLE_LOCAL_BROWSER No false Remove native from the render chain
BROWSERLESS_URL No Browserless service URL when the chain includes browserless
BROWSERLESS_TOKEN No Optional Browserless service token
CF_ACCOUNT_ID No Cloudflare account ID for cf-browser-rendering
CF_BROWSER_RENDERING_TOKEN No Cloudflare Browser Rendering API token
Variable Required Default Description
CONVERT_MAX_FILE_SIZE No 104857600 Max file size for local conversion in bytes (100MB)
CONVERT_ALLOWED_DIRS No Comma-separated paths to restrict local file conversion
Variable Required Default Description
CACHE_DIR No ~/.wet-mcp Data directory for cache, docs, downloads
DOCS_DB_PATH No ~/.wet-mcp/docs.db Docs database location
DOWNLOAD_DIR No ~/.wet-mcp/downloads Media download directory
TOOL_TIMEOUT No 120 Tool execution timeout in seconds (0=no timeout)
WET_CACHE No true Enable/disable web cache
Variable Required Default Description
SYNC_ENABLED No true Enable Google Drive sync
GOOGLE_DRIVE_CLIENT_ID No bundled public client OAuth client ID. HTTP mode auto-uses bundled public Desktop client
GOOGLE_DRIVE_CLIENT_SECRET No bundled public secret OAuth client secret (Desktop public client per Google docs)
SYNC_FOLDER No wet-mcp Google Drive folder name
SYNC_INTERVAL No 300 Auto-sync interval in seconds (0=manual)
Variable Required Default Description
LOG_LEVEL No INFO Logging level
MCP_TRANSPORT No stdio Transport: stdio (default) or http
PUBLIC_URL No HTTP mode: public URL of the server (required for multi-user OAuth)
MCP_DCR_SERVER_SECRET No HTTP mode: random secret for Dynamic Client Registration JWT signing

Set provider keys and endpoints directly as environment variables. A stdio uvx install still needs a configured SearXNG endpoint or cloud search provider for web search; cloud embedding, LLM, and premium search features activate from their corresponding variables. Credentials live only in the local process environment.

After connecting an MCP client to the HTTP endpoint, the client redirects to the relay form on first call:

  1. Open the relay URL in any browser
  2. Fill in API keys on the guided form (all optional)
  3. If SYNC_ENABLED=true, complete the GDrive device-code flow using the bundled public Desktop client (no user OAuth registration needed)
  4. Credentials are encrypted per-JWT-sub and isolated per user

Each user receives an isolated credential vault keyed by JWT sub.

After setup, verify the server is working by calling the search tool:

search(action="search", query="test query", limit=3)

Expected: returns search results with titles, URLs, and snippets.