mnemoai-assistant 1.1.1

Mnemo AI — a local agentic AI assistant (LangGraph + MCP) that learns and remembers, with multi-provider model support.

Mnemo AI

A local agentic AI assistant with MCP (Model Context Protocol) integration, RAG capabilities, and intelligent conversation management. Built on LangGraph with LangChain for multi-provider LLM support (Ollama, Amazon Bedrock, OpenAI, Anthropic, Amazon SageMaker AI, LiteLLM).

▶️ Watch the demo

📖 Documentation

Full documentation is available at https://brunopistone.github.io/mnemoai/

• Getting Started
• Usage
• Configuration
• Advanced Features
• Productivity Tools
• Architecture
• Development

🚀 Quick Start

pip install mnemoai-assistant   # or: uv tool install mnemoai-assistant
mnemoai                          # verbose (shows thinking); --no-verbose to hide

On first run, if no config is found, an interactive configurator launches and walks you through picking a provider, model, and feature toggles — then writes ~/.mnemoai/config/config.yaml.

→ See the Getting Started guide for full setup.

✨ Key Features

• 🤖 Multi-Model Support: Ollama (local), Amazon Bedrock, OpenAI, Anthropic (Claude), Amazon SageMaker AI, LiteLLM (100+ providers)
• 🔧 MCP Tool System: Extensible tool architecture via Model Context Protocol
• 📚 RAG: Automatic document indexing and semantic (hybrid) search
• 🧠 User Profile Learning: Personalized responses learned from interactions
• 🧩 Episodic Memory: Learns from successful task completions and retrieves similar solutions
• 📖 ACE Playbook: Learns strategies from successes AND failures (Agentic Context Engineering)
• 🔍 Web Search & 🌐 Crawler: Brave Search API + web page extraction with RAG ingestion
• 🖼️ Vision Support: Image analysis with vision models
• 📁 File Operations & ✏️ Precise Editing: Read/write/edit text, CSV, JSON, PDF, DOCX
• 🔎 Fast Search: Glob + ripgrep content search (10-100x faster)
• 📋 Todo Tracking, 📝 Plan Mode & 🔄 Background Tasks: Multi-step task management
• ⚡ Bash Execution & 🛡️ Git Safety: Shell commands with smart error handling and guardrails

📄 License

Licensed under the MIT License — see the LICENSE file for details.

🤝 Contributing

This is a personal development project. Feel free to fork and adapt it to your needs; attribution to the original repository is appreciated but not required.