Deterministic semantic memory for local‑first AI systems

⚠️ FIRST READ THIS: The Documentation Policy is the single source of truth for all abstractions, file locations, and developer conventions. All runtime objects are stored in $HOME/.anchor/ and are never in the project root. Read it before coding.

Start here:

1. Documentation Policy - Required read (abstractions, paths, conventions)
2. Project Specs - Architecture, API, data model, test framework
3. Current Standards - Active architecture standards (001-038)

Quick reference:

• Test Framework - How to test (P0, Vitest, integration, operational)
• Test Usability - Automated runtime verification

Start here:

1. Whitepaper - The STAR Context Protocol (conceptual, no code)
2. API Endpoints - Available API routes and usage
3. Architecture Overview - How it works (high-level)

For deeper knowledge:

• STAR Algorithm - The physics-inspired retrieval engine
• Data Model - Compound → Molecule → Atom hierarchy

# Clone and install
git clone https://github.com/RSBalchII/anchor-engine-node
cd anchor-engine-node
pnpm install

# Start the engine
pnpm start

# Run tests
pnpm test

# Start with logging
pnpm start

# Run operational verification
python tests/test_us006.py

Anchor Engine is a semantic memory layer — not an agent framework, not a vector database, and not a cloud service.

It's a deterministic, explainable, CPU‑only system for storing and retrieving long-term memory for AI agents.

It replaces embeddings with a physics‑inspired graph algorithm (STAR) that retrieves context using structure, time, and meaning — not dense vectors.

• ✅ Deterministic retrieval — same query → same result
• ✅ Graph‑based semantics — not probabilistic similarity
• ✅ Temporal decay — older memories naturally fade
• ✅ Provenance receipts — every retrieval comes with proof
• ✅ CPU‑only performance — <1GB RAM, no GPU needed
• ✅ Local‑first architecture — your data never leaves your machine

Use it as:

• A drop‑in replacement for embeddings/vector DBs
• A memory backend for MCP‑compatible agents (Claude, Cursor, Qwen Code)
• A personal knowledge system for long‑term projects

❌ Not an agent framework
❌ Not a cloud service
❌ Not a probabilistic vector search engine
❌ Not a tool that stores your data anywhere except your machine

Most AI memory systems today assume:

• GPU‑heavy vector search
• Probabilistic retrieval
• Cloud dependence
• Opaque similarity metrics

I kept running into the same problem:

I needed a memory system that behaved like a mind, not a search engine.

Anchor Engine is built around three principles:

1. Determinism — same query → same result
2. Explainability — every retrieval comes with provenance
3. Local sovereignty — your data stays on your machine

This project grew out of months of building agents that needed reliable memory — and discovering that existing tools weren't designed for that job.

If you use this software in your research, please cite:

DOI: https://doi.org/10.5281/zenodo.19324840
Citation: Balch II, R. S. (2026). STAR: Semantic Temporal Associative Retrieval - A Local-First Graph-Based Context Engine (v5.0.0). Zenodo.

Software: Anchor Engine Node
License: AGPL-3.0

Anchor Engine uses Rust-compiled WebAssembly modules for performance-critical operations. This eliminates the need for native compilation and provides universal platform support.

Published Packages:

Benefits:

• ✅ Zero native compilation required (works on Windows ARM64, macOS, Linux)
• ✅ ~90% smaller binary size (~1.4 MB WASM vs ~12 MB C++ DLLs)
• ✅ 8x faster module loading (benchmarks: ~50ms vs ~400ms for native)
• ✅ Universal platform support

Note: The older C++ native modules (engine/src/native/ directory) have been deprecated and removed in favor of these Rust WASM packages. See engine/src/README.md for full architectural details.

To protect sensitive QwenPaw agent configuration files from being accidentally committed to the repository, the following files are now gitignored:

• BOOTSTRAP.md
• MEMORY.md
• PROFILE.md
• SOUL.md
• AGENTS.md

These files may contain private information and should never be shared. The .gitignore has been updated to prevent accidental commits of these sensitive configuration files.

• Documentation Policy
• Project Specs
• Current Standards
• Test Framework

• Whitepaper
• API Endpoints
• Architecture Overview

• Automated Testing
• API Endpoints

Repository: https://github.com/RSBalchII/anchor-engine-node
License: AGPL-3.0
Version: 5.3.0 | Production: ✅ Ready