MaxKB

Active
GitHub Python GPL-3.0

Description

MaxKB is an open-source knowledge base Q&A and agent building platform powered by LLMs, with vector retrieval, workflow orchestration, and multi-model support out of the box.

Key Features

  • RAG Pipeline — Document upload and online crawling with automatic splitting and vectorization to reduce hallucinations
  • Agentic Workflow — Powerful workflow engine, function library and MCP tool-use for complex business scenarios
  • Zero-code Integration — Seamlessly integrate into third-party business systems for smart Q&A capabilities
  • Model-Agnostic — Supports DeepSeek, Llama, Qwen, OpenAI, Claude, Gemini and other major models
  • Multi-Modal — Native support for text, image, audio and video input/output
  • One-command Docker deploy — Single Docker command to start, ready out of the box

Use Cases

💡 Enterprise internal knowledge base Q&A system to improve employee information retrieval
💡 Intelligent customer service for automated answers to common questions
💡 Academic research document Q&A for quick retrieval of key points
💡 Educational training Q&A platform for student learning assistance
💡 Cross-modal document analysis for technical docs with charts and figures

Strengths & Limitations

Strengths

  • Actively maintained, recent updates
  • High community interest (22.7k stars)
  • Established track record (2 years in production)
  • Responsive to issues, low backlog

⚠️ Limitations

  • Restrictive license (GPL-3.0)

Quick Start

```bash
# One-command Docker start
docker run -d --name=maxkb --restart=always -p 8080:8080 -v ~/.maxkb:/opt/maxkb 1panel/maxkb

# Access web interface at http://your_server_ip:8080
# Default admin credentials: admin / MaxKB@123..
```

Related Projects

Kotaemon

25.7k · Python
Normal A

Kotaemon is an open-source RAG-based tool for chatting with your documents, featuring a clean chat interface and support for multiple LLM and embedding model backends.

ragdocument-qapdf +2
  • · Hybrid RAG pipeline — combines full-text and vector retrieval with re-ranking for best retrieval quality
  • · Multimodal document QA — supports PDF, HTML, XLSX formats with figure and table extraction from documents
  • · Advanced citations with document preview — relevance-scored citations with in-browser PDF viewer and highlight support

Khoj

37.0k · Python
Normal A

Khoj is a self-hostable AI second brain that answers questions from the web or your docs, builds custom agents, schedules automations, and performs deep research.

second-brainragself-hosted +2
  • · Multi-LLM support — Switch between local and cloud LLMs including llama3, qwen, gemma, mistral, gpt, claude, gemini, deepseek
  • · Multi-format document retrieval — Get answers from PDFs, Markdown, Word, Notion, org-mode, images and more
  • · Custom agent creation — Build custom agents with custom knowledge, persona, chat model and tools

AnythingLLM

65.5k · JavaScript
Active A+

AnythingLLM is an all-in-one AI productivity app with a self-hosted chat UI, RAG knowledge base, AI agents, and multi-model management, privacy-first with zero configuration.

chatbotragknowledge-base +3
  • · Multi-model support — Supports 30+ LLM providers including OpenAI, Anthropic, Ollama, LM Studio, and local llama.cpp models
  • · Dynamic model routing — Automatically routes conversations to the best provider and model based on user-defined rules
  • · AI Agent builder — No-code AI Agent builder with built-in tools like web browsing and MCP protocol compatibility

memU

14.4k · Python
Active A

A memory system for 24/7 proactive agents with MCP protocol integration, providing long-term memory management, skill storage, and proactive reasoning capabilities for continuously running AI agents.

memoryagentmcp +2
  • · 24/7 proactive memory agent that continuously captures and understands user intent
  • · File-system-like memory structure with folders, files, symlinks, and mount points for organized knowledge
  • · Significantly reduces LLM token cost with smaller context windows (~1/10 of comparable usage)