NeuroCore¶
Pluggable, YAML-driven framework for building agentic AI applications.
NeuroCore is the chassis for agentic AI. It wires together workflow orchestration, discoverable skills, structured configuration, and a developer-friendly CLI — so you can focus on building intelligent agents, not plumbing.
Install¶
pip install neurocore-ai
Quick start¶
neurocore init my-agent
cd my-agent
neurocore run blueprints/agent.flow.yaml
Contents¶
Guides
- NeuroCore Developer Tutorial
- What You Will Build
- Table of Contents
- Part 1: Getting Started
- Part 2: Building Your First Skill
- Part 3: Configuration Deep Dive
- Part 4: Blueprints and Flow Orchestration
- Part 5: Adding NeuroWeave (Knowledge Graph Memory)
- Part 6: Chat App — Personal Experiences Collector
- Part 7: Multi-Provider LLM Chat Agent
- Part 8: Multi-Agent Parallel Architecture
- Part 9: Packaging and Distribution
- Part 10: Deployment and Operations
- Part 11: Local Models & Provider Injection
- Part 12: Run History, Replay & Resume
- Part 13: Human-in-the-Loop Approval Gates
- Part 14: Templates & MCP Tools
- Quick Reference
- Concepts
- NeuroCore Architecture
- Table of Contents
- 1. System Overview
- 2. Layer Architecture
- 3. Package Structure
- 4. Class Diagram
- 5. Data Models
- 6. Error Hierarchy
- 7. Configuration Flow
- 8. Config Merging
- 9. Skill Discovery Flow
- 10. Skill Lifecycle
- 11. Blueprint Execution Flow
- 12. CLI Command Flow
- 13. Plugin Architecture
- 14. Component Interaction Matrix
- 15. Key Design Decisions
- 16. LLM Provider Subsystem
- 17. Persistence, Runs & Resume
- 18. Human-in-the-Loop
- Providers
- Persistence & runs
- Human-in-the-loop
- Authoring skills
- NeuroCore vs LangGraph
- Changelog
- API Reference