Status: succeeded
What was built
- engram-protocol core architecture with SQLite + LanceDB storage
- pipeline.py evolution loop using LM Studio LLM endpoint
- MCP server for agent integration
- Memory ingest system for git logs, conversations, and notes
- 4-embeddings recall system with query variations for semantic coverage
Key Decisions
- Chose LM Studio endpoint for local LLM instead of cloud API
- Used LanceDB for local vector search (no server dependency)
- Kept pipeline.py self-contained under 500 lines for evolvability
- Implemented 4-query variations in retrieve() for better recall coverage
Next Steps
- Run evolution cycles to improve pipeline fitness
- Test MCP server integration with various agents
Built from memories
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