Install
$ agentstack add mcp-akougkas-helios-mcp Open-source listing — not yet scanned by AgentStack. Follow the source repository for install instructions.
Security review
⚠ Flagged1 finding(s); flagged for manual review. · v0.1.0 How review works →
- • Prompt-injection patterns
- • Secret / credential exfiltration
- • Dangerous shell & filesystem operations
- • Untrusted network calls
- • Known-malicious package signatures
- high Pipes remote content directly into a shell (remote code execution).
What it can access
- ● Network access Used
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
About
☀️ Helios MCP ☀️
Transform stateless AI into evolving personalities with mathematical precision
[](https://pypi.org/project/helios-mcp/) [](https://www.python.org/downloads/) [](https://opensource.org/licenses/MIT) [](https://modelcontextprotocol.io/) [](https://github.com/akougkas/helios-mcp) [](https://github.com/astral-sh/uv)
[](https://pypi.org/project/helios-mcp/) [](https://github.com/sponsors/akougkas) [](https://discord.gg/helios-mcp)
🚀 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
- [Architecture](docs/ARCHITECTURE.md) - System design and implementation details
- [Development Log](DEVLOG.md) - Progress tracking and technical decisions
- [Configuration Examples](docs/samples/) - 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):
| Tool | Parameters | Returns | Purpose | |------|------------|---------|----------| | get_base_config | None | {base_importance: float, behaviors: dict} | Load foundation configuration | | get_active_persona | name: str | {specialization_level: int, behaviors: dict} | Retrieve persona configuration | | merge_behaviors | base: dict, persona: dict | {merged: dict, weights: dict} | Calculate inheritance | | list_personas | None | [{name: str, level: int}] | List available personas | | update_preference | path: str, value: any | {success: bool} | Modify configuration | | search_patterns | confidence: float | [{pattern: str, score: float}] | Find learned behaviors | | commit_changes | message: str | {commit_id: str} | Version changes | | Learning Tools | | | | | learn_behavior | persona: str, key: str, value: any | {old_value, new_value} | Add/update behaviors | | tune_weight | target: str, parameter: str, value: float | {old_value, new_value} | Adjust weights | | revert_learning | commits_back: int | {reverted_commits} | Undo via git | | evolve_behavior | from: str, to: str, key: str | {direction, value} | Migrate behaviors |
Learning System
Learning tools that directly edit configurations:
learn_behavior(persona, key, value)- Add/update behaviorstune_weight(target, parameter, value)- Adjust inheritance weightsrevert_learning(commits_back)- Undo recent learning via gitevolve_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
| Issue | Solution | |-------|----------| | uvx: command not found | Install UV: curl -LsSf https://astral.sh/uv/install.sh \| sh | | No personas found | Create ~/.helios/personas/default.yaml | | Permission denied | Check write access: ls -la ~/.helios/ | | Git initialization failed | Run git init in ~/.helios/ | | MCP connection failed | Restart your IDE after config changes | | Tool not found | Run 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?
- 📖 [Check our Documentation](docs/ARCHITECTURE.md)
- 🐛 Report a bug
- 💬 GitHub Discussions
🌟 Community & Support
[](https://github.com/akougkas/helios-mcp/discussions) [](https://github.com/akougkas/helios-mcp/issues)
- 🗣️ Discussions: Feature requests and Q&A
- 🐛 Issues: Bug reports and fixes
- 📖 Documentation: [Architecture](docs/ARCHITECTURE.md) and guides
- 🎯 Examples: [Sample Configurations](docs/samples/)
🤝 Contributing
We welcome contributions! See [CONTRIBUTING.md](CONTRIBUTING.md) 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
Report Bug · Request Feature · Documentation
Source & license
This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: akougkas
- Source: akougkas/helios-mcp
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.