AgentIndex icon
AgentIndex
MaxKB logo
MaxKB
★ 23.0k
vs
wet-mcp logo
wet-mcp
★ 19

MaxKB vs wet-mcp

MaxKB: MaxKB is an open-source platform for building enterprise-grade AI agents with integrated RAG pipelines, workflow orchestration, and MCP tool-use capabilities. It supports direct document upload, automatic web crawling, and multiple embedding models for knowledge base construction. Widely used for intelligent customer service, internal knowledge bases, and academic research applications.; 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.

01

TL;DR

MaxKB logo
MaxKBRAG / Knowledge Base · ★ 23.0k
When to choose:
  • You want an all-in-one knowledge-base and workflow agent platform that starts with a single Docker command and embeds easily into websites.
  • You need broad support for domestic Chinese LLM providers alongside global models for internal enterprise Q&A.
When to skip:
  • You cannot use GPL-3.0 licensed software in your commercial distribution; RAGFlow is Apache-2.0.
  • Your primary bottleneck is extracting complex tables and layouts from messy scanned PDFs; RAGFlow's deep document parser goes further.
Read MaxKB full review →
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 →
02

Side-by-Side Comparison

Field
MaxKB logoMaxKB
wet-mcp logowet-mcp
Category
RAG / Knowledge Base
RAG / Knowledge Base
Stars
★ 23.0k
★ 19
License
GPL-3.0
Apache-2.0
Install Command
docker run -d --name=maxkb --restart=always -p 8080:8080 -v ~/.maxkb:/opt/maxkb 1panel/maxkb
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
Updated
1d ago
1d ago
Open Source
Yes
Yes
Website
↗ Visit
↗ Visit
GitHub
↗ GitHub
↗ GitHub
Tags
RAG, Agent, LLM
Web Search, Content Extraction, AI Agent Tooling
03

Features

MaxKB logoMaxKB
01RAG pipeline with document upload, web crawling, and automatic chunking
02Visual workflow builder for multi-step agent logic
03MCP tool-use capabilities for connecting to external services
04Supports multiple LLMs and embedding models
05Docker deployment with 1Panel integration for easy self-hosting
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.
04

Use Cases

MaxKB logoMaxKB
↳Building intelligent customer service bots with enterprise knowledge bases
↳Creating internal Q&A systems over company documents and wikis
↳Deploying research assistants with RAG over academic or technical document collections
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.
05

Best For

MaxKB logoMaxKB
Most PopularEssentialTrending
wet-mcp logowet-mcp
—
FAQ

FAQ

What is the difference between MaxKB and wet-mcp?
Both MaxKB and wet-mcp are in the RAG / Knowledge Base category. MaxKB has 23.0k stars, while wet-mcp has 19 stars.
Which is better, MaxKB or wet-mcp?
The best choice depends on your use case. Choose MaxKB if Building intelligent customer service bots with enterprise knowledge bases, and wet-mcp if AI Agent Research: Enabling AI agents to perform comprehensive web research and academic literature reviews to gather information for complex tasks..
Is MaxKB free or open source?
Yes, MaxKB is open source on GitHub (GPL-3.0).
Is wet-mcp free or open source?
Yes, wet-mcp is open source on GitHub (Apache-2.0).
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