octomind

Crates.iooctomind
lib.rsoctomind
version0.14.0
created_at2025-06-26 03:49:21.565397+00
updated_at2025-09-16 07:21:57.269399+00
descriptionSession-based AI development assistant with conversational codebase interaction, multimodal vision support, built-in MCP tools, and multi-provider AI integration
homepagehttps://octomind.muvon.io
repositoryhttps://github.com/muvon/octomind
max_upload_size
id1726837
size1,737,065
Don Hardman (donhardman)

documentation

https://octomind.muvon.io

README

Octomind 🤖 - AI-Powered Development Assistant

© 2025 Muvon Un Limited | Complete Documentation

Session-based AI development assistant with conversational codebase interaction, multimodal vision support, built-in MCP tools, and multi-provider AI integration

Octomind is a session-first AI development assistant that transforms how you interact with codebases through natural language conversations. Built on the Model Context Protocol (MCP), it provides seamless integration with development tools, multi-provider AI support, and intelligent cost optimization.

asciicast

✨ Core Features

  • 🎯 Session-First Architecture - Everything happens in interactive AI conversations with persistent context
  • 🛠️ Built-in MCP Tools - File operations, code analysis, shell commands, web search via Model Context Protocol
  • 🌐 Multi-Provider AI Support - OpenRouter, OpenAI, Anthropic, Google, Amazon, Cloudflare, DeepSeek
  • 🖼️ Multimodal Vision Support - Analyze images, screenshots, diagrams with AI vision capabilities
  • 💰 Cost Tracking & Optimization - Real-time usage monitoring, caching, and detailed cost reporting
  • 🔧 Role-Based Configuration - Developer (full tools), Assistant (chat-only), and custom roles
  • 🧠 Smart Session Continuation - Automatic context management when token limits are reached
  • Layered Processing - AI pipeline system for complex task decomposition and processing

🚀 Quick Start

Prerequisites

  • API Key from supported AI provider

Installation

# One-line install (recommended)
curl -fsSL https://raw.githubusercontent.com/muvon/octomind/master/install.sh | bash

# Set your AI provider API key (choose one)
export OPENROUTER_API_KEY="your_key"     # Multi-provider access
export OPENAI_API_KEY="your_key"         # Direct OpenAI
export ANTHROPIC_API_KEY="your_key"      # Direct Anthropic

# Start your first session
octomind session

💬 How It Works

Octomind operates through interactive AI sessions with built-in development tools:

> "How does authentication work in this project?"
[AI analyzes project structure, finds auth-related files, explains implementation]

> "Add error handling to the login function"
[AI examines login code, implements error handling, shows changes]

> "Rename 'processData' to 'processUserData' across all files"
[AI finds all occurrences, performs batch edit across multiple files]

> /image screenshot.png
> "What's wrong with this UI layout?"
[AI analyzes the image, identifies layout issues, suggests CSS fixes]

> agent_context_gatherer(task="Analyze the authentication system architecture")
[Routes task to specialized context gathering AI agent with development tools]

> /report
[Shows: $0.02 spent, 3 requests, 5 tool calls, timing analysis]

Built-in MCP Tools

  • Developer Tools: shell(), ast_grep() - Execute commands and search code patterns
  • Filesystem Tools: text_editor(), list_files(), batch_edit() - File operations
  • Web Tools: web_search(), read_html() - Web research and content analysis
  • Agent Tools: agent_*() - Route tasks to specialized AI processing layers

Session Commands

  • /help - Show available commands
  • /info - Display token usage and costs
  • /image <path> - Attach images for AI analysis
  • /mcp info - Check MCP server status
  • /model <model> - Switch AI models
  • /role <role> - Change role (developer/assistant)
  • /cache - Add cache checkpoint for cost optimization

🌐 Supported AI Providers

Provider Format Features
OpenRouter openrouter:provider/model Multi-provider access, caching, vision models
OpenAI openai:model-name Direct API, cost calculation, GPT-4o vision
Anthropic anthropic:model-name Claude models, caching, Claude 3+ vision
Google google:model-name Vertex AI, Gemini 1.5+ vision support
Amazon amazon:model-name Bedrock models, AWS integration, Claude vision
Cloudflare cloudflare:model-name Edge AI, fast inference, Llama 3.2 vision
DeepSeek deepseek:model-name Cost-effective models, competitive performance

🛠️ Installation & Setup

Prerequisites

  • Rust 1.82+ and Cargo
  • API Key from supported AI provider

Installation Options

# One-line install (recommended)
curl -fsSL https://raw.githubusercontent.com/muvon/octomind/master/install.sh | bash

# Build from source (for development)
git clone https://github.com/muvon/octomind.git
cd octomind
cargo build --release

# Install via Cargo (when published)
cargo install octomind

API Key Setup

Set your AI provider API key (choose one or more):

# Multi-provider access (recommended)
export OPENROUTER_API_KEY="sk-or-v1-..."

# Direct provider access
export OPENAI_API_KEY="sk-..."
export ANTHROPIC_API_KEY="sk-ant-..."
export GOOGLE_API_KEY="AIza..."
export AMAZON_ACCESS_KEY_ID="AKIA..."
export AMAZON_SECRET_ACCESS_KEY="..."
export CLOUDFLARE_API_TOKEN="..."
export DEEPSEEK_API_KEY="sk-..."

# Optional: Web search capability
export BRAVE_API_KEY="BSA..."

First Run

# Generate default configuration (optional)
octomind config

# Start your first session
octomind session

# Within the session, try:
/help                    # Show all available commands
/info                    # Check token usage and costs
/mcp info               # Check MCP tool status

🎮 Session Commands

Essential commands for interactive sessions:

Core Commands

  • /help - Show available commands
  • /info - Display token usage and costs
  • /image <path> - Attach images for AI analysis
  • /model [model] - View or change AI model
  • /role [role] - Change role (developer/assistant)

Context Management

  • /cache - Add cache checkpoint for cost optimization
  • /context [filter] - Display session context
  • /truncate - Manually truncate context
  • /done - Finalize task with memorization

MCP Tools & Debugging

  • /mcp info - Check MCP server status
  • /run <command> - Execute custom commands
  • /layers - Toggle layered processing
  • /loglevel [level] - Set logging level

Session Management

  • /save - Save current session

  • /clear - Clear terminal screen

  • /exit - Exit session

🏗️ Architecture

Session-First Design: Everything happens in interactive AI conversations with persistent context and built-in development tools.

Core Components:

  • MCP Tools: Built-in servers for development (shell, ast_grep), filesystem (text_editor, batch_edit), web (search, html), and agent routing
  • Multi-Provider AI: Seamless switching between OpenRouter, OpenAI, Anthropic, Google, Amazon, Cloudflare, DeepSeek
  • Role-Based Access: Developer (full tools), Assistant (chat-only), and custom role configurations
  • Smart Caching: Automatic cost optimization with cache markers and intelligent context management
  • Layered Processing: AI pipeline system for complex task decomposition and specialized processing

🔧 Configuration

Octomind uses a template-based configuration system with smart defaults:

# Generate default config (optional)
octomind config

# View current settings
octomind config --show

# Validate configuration
octomind config --validate

Configuration Features:

  • Template-Based: All defaults in config-templates/default.toml
  • Environment Overrides: Any setting can be overridden with OCTOMIND_* variables
  • Role-Based: Different configurations for developer/assistant/custom roles
  • MCP Integration: Built-in and external MCP server configurations
  • Cost Controls: Spending thresholds and performance tuning

📖 Documentation

📚 Complete Documentation - Comprehensive guides and references

Quick Navigation

🚀 Contributing

Contributions are welcome! Help make Octomind better for the development community.

Development Setup:

git clone https://github.com/muvon/octomind.git
cd octomind
cargo check --message-format=short    # Fast compilation check
cargo clippy --all-features --all-targets -- -D warnings  # Fix code quality
cargo build                           # Build when needed

Development Areas:

  • AI Providers: Add new providers in src/providers/
  • MCP Tools: Extend built-in tools in src/mcp/
  • Session Features: Enhance session management in src/session/
  • Documentation: Improve guides and examples

Requirements: Rust 1.82+, API key from supported providers

🆘 Troubleshooting

Common Issues:

  • Build Errors: Use cargo check --message-format=short for fast syntax checking
  • Missing API Keys: Set OPENROUTER_API_KEY or provider-specific keys
  • Invalid Model Format: Use provider:model format (e.g., openrouter:anthropic/claude-sonnet-4)
  • MCP Tool Issues: Check /mcp info for server status
  • Session Problems: Use /loglevel debug for detailed logging

Getting Help:

📞 Support & Contact

⚖️ License

Apache License 2.0 Copyright © 2025 Muvon Un Limited

Commit count: 675

cargo fmt