mindcore 0.1.0

Pluggable, feature-gated memory engine for AI agent applications
Documentation

MindCore

A standalone Rust crate providing a pluggable, feature-gated memory engine for AI agent applications.

Handles persistent storage, keyword search (FTS5), vector search (candle), hybrid retrieval (RRF), graph relationships, memory consolidation, cognitive decay modeling, and token-budget-aware context assembly.

Design Principles

  • Library, not framework — projects call into MindCore, not the other way around
  • Feature-gated everything — heavy dependencies behind compile-time flags
  • Local-first — SQLite-backed, single-file databases, no cloud dependency
  • Pure Rust where possible — candle over ort, SQLite over Postgres
  • Proven patterns only — every component is battle-tested in production

Status

Architecture and research phase. See:

  • MINDCORE_ARCHITECTURE.md — full crate structure and API design
  • MINDCORE_RESEARCH.md — research, landscape analysis, and specification
  • DECISIONS.md — architectural decisions log
  • research/ — competitive landscape analysis

Origin

MindCore extracts and unifies patterns from three projects:

Source Contribution
Memloft Hybrid search (RRF), candle embeddings, FallbackBackend, background indexing
Dial FTS5 + Porter stemming, trust scoring, token-budget context assembly
PIRDLY Two-tier memory (global + project), error classification, MCP server interface