Anneal Memory MCP server

<!-- mcp-name: io.github.phillipclapham/anneal-memory -->

anneal-memory

Living memory for AI agents. Episodes compress into identity.

Memory without grounding is amplification infrastructure.

Persistent user memory profiles increase agent sycophancy 16–45% across models (Gemini 2.5 Pro at 45%, others lower). Production deployments accumulate 97.8% junk entries within weeks. Clinical research documents memory scaffolding delusions across sessions00396-7). The failure mode here isn't memory. It's memory with nothing checking what gets kept.

anneal-memory adds structural defenses at the citation layer that the systems surveyed below don't ship. Patterns earn promotion through cited episode evidence with lexical-overlap explanation-grounding, fabricated citations get demoted, per-ID citation gaming surfaces a flag, replay attempts against stale episodes fail by construction, and the audit chain is SHA-256 hash-chained and tamper-evident. Stale patterns surface for the agent to act on; associations form through consolidation. These are narrow, structural primitives — not a complete defense against every form of memory drift. See Honest scope below for what these primitives catch and what they don't.

And it's memory you own and govern. A local store, zero dependencies, no vendor in the loop — you decide what graduates into long-term memory, every change is recorded in a tamper-evident chain (best-effort on the write side — see Hash-chained audit trail for what verify can and cannot see), and the consolidation step that rewrites an agent's identity is gated to a human, not run unbidden (the Single-consolidator gate below). Own the substrate; govern what enters it.

Four cognitive layers — episodic store, compressed continuity, Hebbian associations, affective state tracking — plus two sibling stores: prospective spores (what the agent intends to do next) and a crystallized pattern store (graduated wisdom held out of always-loaded context and recalled on cue, so a large body of proven knowledge stays effective without clogging attention). Together they implement Complementary Learning Systems — see The Memory Architecture below. Zero dependencies (Python stdlib only). Works with any agent framework.

Quick Start

pip install anneal-memory

Windows

anneal-memory runs on Windows. What to know:

Shortened. The full README is on GitHub.