AgentIndex icon
AgentIndex
wet-mcp logo
wet-mcp
★ 19
vs
extract-llms-docs logo
extract-llms-docs
★ 35

wet-mcp vs extract-llms-docs

wet-mcp: WET - Web Extended Toolkit MCP Server provides AI agents with comprehensive capabilities for web search, content extraction, and library documentation retrieval. It features a 5-strategy scraping chain, integrated metasearch, and zero-configuration local models for embeddings and reranking, operating without requiring API keys.; extract-llms-docs: llm.energy is a web application and MCP server designed to fetch, parse, and organize documentation from websites following llms.txt and install.md standards. It transforms this raw documentation into structured, agent-ready formats for AI assistants, LLMs, and developer tooling.

01

TL;DR

wet-mcp logo
wet-mcpRAG / Knowledge Base · ★ 19

AI Agent Research: Enabling AI agents to perform comprehensive web research and academic literature reviews to gather information for complex tasks.

Read wet-mcp full review →
extract-llms-docs logo
extract-llms-docsRAG / Knowledge Base · ★ 35

Feed documentation directly to AI coding assistants for enhanced context.

Read extract-llms-docs full review →
02

Side-by-Side Comparison

Field
wet-mcp logowet-mcp
extract-llms-docs logoextract-llms-docs
Category
RAG / Knowledge Base
RAG / Knowledge Base
Stars
★ 19
★ 35
License
Apache-2.0
NOASSERTION
Install Command
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
git clone https://github.com/nirholas/extract-llms-docs.git && cd extract-llms-docs && pnpm install
Updated
2d ago
3d ago
Open Source
Yes
Yes
Website
↗ Visit
↗ Visit
GitHub
↗ GitHub
↗ GitHub
Tags
Web Search, Content Extraction, AI Agent Tooling
Documentation Extraction, AI Agent Tooling, LLM Integration
03

Features

wet-mcp logowet-mcp
01Web Search: Embedded SearXNG metasearch (Google, Bing, DuckDuckGo, Brave) with query expansion, TTL cache, and standardized citation format. Optional cloud search backends.
02Content Extract: 5-strategy escalation chain for URL content extraction, providing smart chunks structured output (clean text, markdown, JSON-LD, code blocks, metadata), batch processing, deep crawling, and local file conversion.
03Library Docs: Auto-discover and index documentation with FTS5 hybrid search, HyDE-enhanced retrieval, and version-specific docs for AI agents.
04Zero Config: Built-in local Qwen3 embedding + reranking, no API keys needed. Optional cloud providers can be selected per task for higher-quality results.
extract-llms-docs logoextract-llms-docs
01Smartly detects llms.txt and install.md standards on websites.
02Transforms documentation into agent-ready formats, including an AGENT-GUIDE.md.
03Supports exporting documentation in Markdown, JSON, YAML, or ZIP formats.
04AI-powered generation of install.md instructions from GitHub repos or documentation URLs.
05Provides an MCP server for integration with AI clients like Claude Desktop and Cursor.
04

Use Cases

wet-mcp logowet-mcp
↳AI Agent Research: Enabling AI agents to perform comprehensive web research and academic literature reviews to gather information for complex tasks.
↳Structured Data Extraction: Automatically extracting structured and unstructured data from web pages, including clean text, markdown, JSON-LD, and code blocks, for further processing by agents.
↳Developer Documentation Access: Providing AI agents with version-aware and topic-specific access to software library documentation for code generation, debugging, or learning.
↳Offline Content Processing: Converting local files (PDF, DOCX, HTML, etc.) to Markdown for AI agent consumption, enabling analysis of local knowledge bases.
extract-llms-docs logoextract-llms-docs
↳Feed documentation directly to AI coding assistants for enhanced context.
↳Build AI agents with up-to-date documentation for improved context-awareness.
↳Establish documentation pipelines specifically for Retrieval-Augmented Generation (RAG) systems.
↳Automatically aggregate documentation from various sources.
↳Generate llms.txt and install.md instructions for new or existing projects.
FAQ

FAQ

What is the difference between wet-mcp and extract-llms-docs?
Both wet-mcp and extract-llms-docs are in the RAG / Knowledge Base category. wet-mcp has 19 stars, while extract-llms-docs has 35 stars.
Which is better, wet-mcp or extract-llms-docs?
The best choice depends on your use case. Choose wet-mcp if AI Agent Research: Enabling AI agents to perform comprehensive web research and academic literature reviews to gather information for complex tasks., and extract-llms-docs if Feed documentation directly to AI coding assistants for enhanced context..
Is wet-mcp free or open source?
Yes, wet-mcp is open source on GitHub (Apache-2.0).
Is extract-llms-docs free or open source?
Yes, extract-llms-docs is open source on GitHub (NOASSERTION).
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