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About agentmemory-architecture

A

agentmemory-architecture

How agentmemory is built, the iii engine primitives it runs on, its storage

Agentmemory-architecture explains how agentmemory is built and how it stores what it remembers. Agentmemory is a memory server for coding agents that runs locally, captures observations, indexes them for hybrid retrieval and serves them back over REST and MCP. It is built on the iii engine, where everything is a function, a trigger or worker state, and new capabilities are added as a new function plus a trigger rather than through a separate plugin system. Recall combines BM25 keyword search with configured vector similarity and graph expansion. A clean installation without an embedding provider uses BM25 and needs no API key, and on-device embeddings can be turned on with an environment setting. Memories carry content, concepts, files, importance and timestamps, and are grouped into sessions and optionally linked to commits. A lifecycle of capture, compression, consolidation and forgetting keeps the store useful over time. The skill also lists the default ports and the viewer. It is used when reasoning about how memory is stored or why retrieval behaves the way it does.

View agentmemory-architectureAll AI Skills apps
Price
Free
Made by
rohitg00
Category
AI Skills
Website
github.com/rohitg00/agentmemory/agentmemory-architecture