Back to work
AI Memory Engine MCP Server v0.4.0 Active Development

Hybrid Cognitive Runtime

A persistent AI agent memory system where agents never repeat the same mistake twice. Causal event replay, cognitive state objects, and 40+ MCP tools — achieving 41% token savings against stateless baselines.

By the Numbers

The Problem

AI agents are stateless. Every conversation starts from zero. They repeat mistakes, lose context across sessions, and can't build on prior reasoning. This makes them unreliable for anything that requires persistent understanding — which is most real-world tasks.

HCR solves this by giving agents a structured, persistent memory system. Not just storing chat logs — building a cognitive state graph that captures causal relationships between events, decisions, and outcomes.

Architecture

The runtime is built around three core primitives: Cognitive State Objects (CSOs) that snapshot the agent's full reasoning context, a causal event graph that tracks how decisions lead to outcomes, and BOCPD-based episode segmentation that detects when the agent's working context has shifted.

The MCP server exposes 40+ tools that allow any Claude Code or MCP-compatible client to read and write cognitive state. Agents can replay prior reasoning chains, recall similar problem patterns, and avoid previously-failed approaches — all through standard tool calls.

Key Features

Tech Stack

Python · FastAPI · MCP SDK · SQLite · NetworkX · Pydantic · pytest · Docker · CI/CD