# MnemoCore Roadmap

**Open Source Infrastructure for Persistent Cognitive Memory**

Version: 4.5.0-beta | Updated: 2026-02-20

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## Vision

MnemoCore provides the foundational memory layer for cognitive AI systems —
a production-ready, self-hosted alternative to cloud-dependent memory solutions.

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## Current Status (v4.5.0-beta)

| Component | Status |
|-----------|--------|
| Binary HDV Engine | ✅ Stable |
| Tiered Storage (HOT/WARM/COLD) | ✅ Functional |
| HNSW Index | ✅ Working |
| Query/Store API | ✅ Operational |
| Qdrant Integration | ✅ Available |
| MCP Server | 🟡 Beta |
| PyPI Distribution | 🟡 Pending |

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## Phase 5: Production Hardening

**Goal:** Battle-tested, enterprise-ready release

### 5.1 Stability & Testing
- [ ] Increase test coverage to 80%+
- [ ] Add integration tests for Qdrant backend
- [ ] Stress test with 100k+ memories
- [ ] Add chaos engineering tests (network failures, disk full)

### 5.2 Performance Optimization
- [ ] Benchmark query latency at scale
- [ ] Optimize HNSW index rebuild time
- [ ] Add batch operation endpoints
- [ ] Profile and reduce memory footprint

### 5.3 Developer Experience
- [ ] Complete API documentation (OpenAPI spec)
- [ ] Add usage examples for common patterns
- [ ] Create quickstart guide
- [ ] Add Jupyter notebook tutorials

### 5.4 Operations
- [ ] Docker Compose production config
- [ ] Kubernetes Helm chart
- [ ] Prometheus metrics endpoint
- [ ] Health check hardening

**ETA:** 2-3 weeks

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## Phase 6: Feature Expansion

**Goal:** More cognitive capabilities

### 6.1 Advanced Retrieval
- [ ] Temporal queries ("memories from last week")
- [ ] Multi-hop associative recall
- [ ] Contextual ranking (personalized relevance)
- [ ] Negation queries ("NOT about project X")

### 6.2 Memory Enrichment
- [ ] Auto-tagging via LLM
- [ ] Entity extraction (names, dates, concepts)
- [ ] Sentiment scoring
- [ ] Importance classification

### 6.3 Multi-Modal Support
- [ ] Image embedding storage
- [ ] Audio transcript indexing
- [ ] Document chunk management

**ETA:** 4-6 weeks

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## Phase 7: Ecosystem

**Goal:** Easy integration with existing AI stacks

### 7.1 Integrations
- [ ] LangChain memory adapter
- [ ] LlamaIndex integration
- [ ] OpenAI Assistants API compatible
- [ ] Claude MCP protocol

### 7.2 SDKs
- [ ] Python SDK (official)
- [ ] TypeScript/JavaScript SDK
- [ ] Go SDK
- [ ] Rust SDK

### 7.3 Community
- [ ] Discord/Slack community
- [ ] Contributing guide
- [ ] Feature request process
- [ ] Regular release cadence

**ETA:** 8-12 weeks

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## Long-Term Vision (Phase 8+)

### Research Directions
- [ ] Hierarchical memory (episodic → semantic → procedural)
- [ ] Forgetting curves with spaced repetition
- [ ] Dream consolidation during idle cycles
- [ ] Meta-learning from usage patterns

### Platform
- [ ] Managed cloud offering (optional)
- [ ] Multi-tenant support
- [ ] Federation across nodes
- [ ] Privacy-preserving memory sharing

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## Release Schedule

| Version | Target | Focus |
|---------|--------|-------|
| v4.5.0 | Current | Beta stabilization |
| v5.0.0 | +2 weeks | Production ready |
| v5.1.0 | +4 weeks | Performance + DX |
| v6.0.0 | +6 weeks | Feature expansion |
| v7.0.0 | +10 weeks | Ecosystem |

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## Contributing

MnemoCore is open source under MIT license.

- **GitHub:** https://github.com/RobinALG87/MnemoCore-Infrastructure-for-Persistent-Cognitive-Memory
- **PyPI:** `pip install mnemocore`
- **Issues:** Use GitHub Issues for bugs and feature requests
- **PRs:** Welcome! See CONTRIBUTING.md

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*Roadmap maintained by Robin Granberg & Omega*