ContextForge: Architecture-First Persistent Agentic Memory via Model Context Protocol — Multi-Trigger OR-Gate Security, OR-Set CRDT Sync, Tri-Core Failover, Differential Context Injection, Recency-Weighted Retrieval, and a Memory Quality Benchmark

ContextForge v2.3 — Nexus MCP Server: Supplementary Materials ContextForge is a five-pillar agentic memory architecture that closes three structural failure modes of stateless RAG systems: zero adversarial block rate, high failover latency, and unbounded context injection. It exposes all capabilities as a 22-tool Model Context Protocol (MCP) server — delivering persistent, adversarially-hardened memory across Claude Desktop, Cursor, VS Code, and Windsurf with zero client-side changes. This record contains the supplementary data, benchmark results, figures, and source code for the paper "ContextForge: Architecture-First Persistent Agentic Memory via Model Context Protocol — Multi-Trigger OR-Gate Security, OR-Set CRDT Sync, Tri-Core Failover, Differential Context Injection, Recency-Weighted Retrieval, and a Memory Quality Benchmark". Key Results Security / Injection Defense (Suite 14, n = 300) Attack Block Rate (ABR): 55% at benign FPR = 1% (vs 25% FPR in v1 PAPER mode, −24 pp) Edge-case FPR: 16% (vs ~97% in v1 PAPER mode, −81 pp) External validation macro-F1: 75.5% (deepset/prompt-injections dataset) Composite Safety Index Φ = 79.7% Memory Integrity (Suite 15 v2, n = 160, 6-system comparison) Memory Integrity Score (MIS): 0.8012 — mean(Recall@3, UpdateAccuracy, DeleteAccuracy, PoisonResistance) Update accuracy: 0.229 → 0.600 (+37.1 pp) via recency-weighted BM25 (score = BM25 × exp(−λ·age), λ = 0.0001 s⁻¹) Operating Modes The ReviewerGuard v3 OR-Gate ships two modes selectable via CF_MODE: paper (default) — word-level entropy H* = 3.5, exact paper reproduction experiment — char-level entropy H* = 4.8, soft Pass 2, auto-perplexity gate (P* = 231.8), reducing edge-case FPR from ~97% to 16% Archive Contents benchmark_results.zip — All benchmark JSON outputs (Suites 7–12, 14, 15; security comparison tables) figures.zip — Publication figures (PNG) + Python generator scripts for full reproducibility source_code.zip — Core Python modules, LaTeX paper source, and bibliography Reproducibility pip install -r requirements.txt # Full v5.0 benchmark suite (375 tests) python -X utf8 benchmark/test_v5/run_all.py # Suite 14 — FPR fix evaluation (300 samples × 5 baselines) python -X utf8 benchmark/suites/suite_14_fpr_fix_eval.py # Regenerate all paper figures python research/figures/gen_all.py License: MITRepository: https://github.com/parnish007/contextforge