helios-mcp

akougkas/helios-mcp

3.2

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Helios MCP is a model context protocol server designed to give AI agents persistent personalities, learned behaviors, and evolving capabilities through a git-versioned behavioral management system.

☀️ Helios MCP ☀️

Transform stateless AI into evolving personalities with mathematical precision

PyPI Python 3.13+ License: MIT MCP 2025 Tests Built with UV

Install with uvx GitHub Sponsors Discord

🚀 What is Helios?

Helios is a configuration persistence engine that gives AI agents long-term memory and evolving personalities through weighted behavioral inheritance. Unlike RAG systems that retrieve knowledge, Helios manages how your AI behaves, not what it knows.

The Problem It Solves

Every AI conversation today starts from zero. You explain your preferences, working style, and context repeatedly. Your AI assistant has no memory of who you are or how you like to work. Helios changes that.

The Solution

Helios provides a mathematical framework for AI personality evolution:

  • Base configurations define core behaviors (70% influence)
  • Specialized personas adapt to specific contexts (30% influence)
  • Learning system captures patterns from actual usage
  • Git versioning tracks every behavioral change

This isn't prompt engineering - it's personality engineering.

⚡ Installation & Setup

🚀 Quick Install (30 seconds)

# One command to rule them all
uvx helios-mcp

That's it! Helios is now available as an MCP server.

📱 IDE Integration

✨ Cursor (Recommended)

Add to ~/.cursor/mcp.json:

{
  "mcpServers": {
    "helios": {
      "command": "uvx",
      "args": ["helios-mcp", "--helios-dir", "~/.helios"]
    }
  }
}
🔵 Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "helios": {
      "command": "uvx",
      "args": ["helios-mcp", "--helios-dir", "~/.helios"]
    }
  }
}
💻 VS Code / Claude Code

Add to your VS Code settings.json:

{
  "mcp.servers": {
    "helios": {
      "command": "uvx",
      "args": ["helios-mcp"]
    }
  }
}
🌊 Windsurf

Add to your Windsurf MCP config:

{
  "mcpServers": {
    "helios": {
      "command": "uvx",
      "args": ["helios-mcp", "--helios-dir", "~/.helios"]
    }
  }
}
🔧 Development Setup

For contributors and local development:

# Clone and setup
git clone https://github.com/akougkas/helios-mcp
cd helios-mcp
uv sync

# Run locally
uv run helios-mcp --verbose

🎯 First Time Setup

After installation, create your first persona:

# Helios will create ~/.helios/ automatically on first run
mkdir -p ~/.helios/personas

Create ~/.helios/personas/developer.yaml:

specialization_level: 2
behaviors:
  communication_style: "Concise with code examples"
  problem_solving: "Test-driven, iterative" 
  preferred_tools: ["pytest", "uv", "ruff"]

🎉 Done! Your AI now has persistent memory and personality.

✨ Features

🧬 Weighted Inheritance Model

# The core formula that powers Helios
inheritance_weight = base_importance / (specialization_level ** 2)
final_behavior = base * inheritance_weight + persona * (1 - inheritance_weight)

🎯 Multi-Persona Support

  • Developer: Technical, test-driven, loves clean code
  • Researcher: Academic, citation-focused, methodical
  • Creative: Imaginative, narrative-driven, experimental
  • Custom: Define any personality you need

📊 Git-Powered Memory

  • Every configuration change is versioned
  • Roll back to any previous personality state
  • Track behavioral evolution over time
  • Collaborative persona development

🔧 MCP Native

Built specifically for the Model Context Protocol with 11 powerful tools for AI agents to manage their own evolution (7 core + 4 learning).

📚 Documentation

  • - System design and implementation details
  • - Progress tracking and technical decisions
  • - Sample base and persona configurations

🤖 AI Agent Integration Guide

This section provides detailed technical information for AI agents using Helios MCP.

Available MCP Tools

Helios exposes 11 tools through the Model Context Protocol (7 core + 4 learning):

ToolParametersReturnsPurpose
get_base_configNone{base_importance: float, behaviors: dict}Load foundation configuration
get_active_personaname: str{specialization_level: int, behaviors: dict}Retrieve persona configuration
merge_behaviorsbase: dict, persona: dict{merged: dict, weights: dict}Calculate inheritance
list_personasNone[{name: str, level: int}]List available personas
update_preferencepath: str, value: any{success: bool}Modify configuration
search_patternsconfidence: float[{pattern: str, score: float}]Find learned behaviors
commit_changesmessage: str{commit_id: str}Version changes
Learning Tools
learn_behaviorpersona: str, key: str, value: any{old_value, new_value}Add/update behaviors
tune_weighttarget: str, parameter: str, value: float{old_value, new_value}Adjust weights
revert_learningcommits_back: int{reverted_commits}Undo via git
evolve_behaviorfrom: str, to: str, key: str{direction, value}Migrate behaviors

Learning System

Learning tools that directly edit configurations:

  • learn_behavior(persona, key, value) - Add/update behaviors
  • tune_weight(target, parameter, value) - Adjust inheritance weights
  • revert_learning(commits_back) - Undo recent learning via git
  • evolve_behavior(from, to, key) - Promote behaviors between configs

All learning is tracked through git, providing complete history and rollback capability.


💡 Use Cases

Real-World Scenarios

Software Development Team

  • Morning: Load "architect" persona for system design
  • Afternoon: Switch to "debugger" for troubleshooting
  • Code review: Use "mentor" persona for teaching

Research & Writing

  • Literature review: "researcher" persona
  • Data analysis: "statistician" persona
  • Paper writing: "academic_writer" persona

Personal Assistant

  • Work hours: Professional, formal communication
  • Personal time: Casual, friendly interaction
  • Learning mode: Patient, educational approach

🛠️ Development

# Clone and setup
git clone https://github.com/akougkas/helios-mcp
cd helios-mcp
uv sync

# Run tests (159 tests passing)
uv run pytest

# Run with local changes
uv run helios-mcp --verbose

Tech Stack

  • Python 3.13 with JIT compiler
  • FastMCP 2.2.6+ for MCP protocol
  • UV for dependency management
  • Git for versioning
  • YAML for configurations

🐛 Troubleshooting

Common Issues & Solutions
IssueSolution
uvx: command not foundInstall UV: curl -LsSf https://astral.sh/uv/install.sh | sh
No personas foundCreate ~/.helios/personas/default.yaml
Permission deniedCheck write access: ls -la ~/.helios/
Git initialization failedRun git init in ~/.helios/
MCP connection failedRestart your IDE after config changes
Tool not foundRun uvx helios-mcp or check PATH

Debug Commands:

# Verify installation
uvx helios-mcp --version

# Test with verbose logging  
uvx helios-mcp --verbose

# Check your personas
ls -la ~/.helios/personas/

# Validate YAML syntax
uv run python -c "import yaml; yaml.safe_load(open('~/.helios/base/identity.yaml'))"

Still having issues?

🌟 Community & Support

GitHub Discussions GitHub Issues

  • 🗣️ Discussions: Feature requests and Q&A
  • 🐛 Issues: Bug reports and fixes
  • 📖 Documentation: and guides
  • 🎯 Examples:

🤝 Contributing

We welcome contributions! See for guidelines.

Quick Contribution

# Fork, clone, branch
git checkout -b feature/your-feature

# Make changes, test
uv run pytest

# Submit PR
gh pr create

📄 License

MIT © 2025 Anthony Kougkas

🙏 Acknowledgments

Built for the Model Context Protocol ecosystem. Special thanks to the MCP community and early adopters.


Transform your AI from stateless to sophisticated

uvx helios-mcp

Built with ☀️ by humans, for AI

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