agentmemory-architecture

Agent Skills › rohitg00/agentmemory › agentmemory-architecture

agentmemory-architecture

GitHub

AgentMemory 是面向编码代理的本地内存服务器，基于 iii 引擎构建。它通过混合检索（BM25+向量）存储和提取记忆，提供 REST/MCP 接口及实时 Web 查看器，支持记忆的生命周期管理。

plugin/skills/agentmemory-architecture/SKILL.md rohitg00/agentmemory

Trigger Scenarios

查询 AgentMemory 的内部架构或工作原理配置或调试 AgentMemory 的端口、存储模型及检索功能扩展 AgentMemory 系统以添加新功能

Install

npx skills add rohitg00/agentmemory --skill agentmemory-architecture -g -y

More Options

Non-standard path

npx skills add https://github.com/rohitg00/agentmemory/tree/main/plugin/skills/agentmemory-architecture -g -y

Use without installing

npx skills use rohitg00/agentmemory@agentmemory-architecture

指定 Agent (Claude Code)

npx skills add rohitg00/agentmemory --skill agentmemory-architecture -a claude-code -g -y

安装 repo 全部 skill

npx skills add rohitg00/agentmemory --all -g -y

预览 repo 内 skill

npx skills add rohitg00/agentmemory --list

SKILL.md

Frontmatter

{
    "name": "agentmemory-architecture",
    "description": "How agentmemory is built, the iii engine primitives it runs on, its storage model, ports, and the viewer. Use when reasoning about how memory is stored or retrieved end to end, when extending the system, or when answering how agentmemory works under the hood.",
    "user-invocable": false
}

agentmemory is a memory server for coding agents. It runs locally, captures observations, indexes them for hybrid retrieval, and serves them back over REST and MCP. Worker Compose runs the pinned iii engine with AgentMemory and the registry state and http workers. The state worker uses a file-backed KV store by default, with Redis available by configuration; it is not SQLite.

iii primitives

Everything is a function, a trigger, or worker state on the iii engine. There is no separate plugin system; the worker registers functions (mem::*) and HTTP triggers (api::*) and the engine routes calls. agentmemory does not bypass iii; new capability is a new function plus a trigger.

Retrieval model

Recall combines BM25 keyword search with configured vector similarity and graph expansion. A clean installation has no embedding provider and uses BM25 without an API key. Set EMBEDDING_PROVIDER=local to enable on-device embeddings, which download a model once. A remote embedding provider runs only when EMBEDDING_PROVIDER names it. LLM summaries, consolidation and reflection run only when AGENTMEMORY_LLM_PROVIDER selects a provider or AGENTMEMORY_ALLOW_AGENT_SDK=true turns on the Claude Agent SDK fallback; a key in the environment alone does not turn them on. Per-observation LLM compression also needs AGENTMEMORY_AUTO_COMPRESS=true.

Data boundary

Captured prompts, tool inputs and outputs, and memories stay in the local store. They leave the machine only through options the user turns on: a selected LLM provider, the Agent SDK fallback (AGENTMEMORY_ALLOW_AGENT_SDK=true), a remote embedding provider, a Redis state backend, or mesh sync to peer servers the user registers.

Storage and lifecycle

Memories carry content, concepts, files, importance, and timestamps, grouped into sessions and optionally linked to commits. A lifecycle of capture, compress, consolidate, and forget keeps the store useful over time rather than letting it grow unbounded.

Ports

REST defaults to port 3111, the viewer to 3113, and the internal engine WebSocket to 49134. Use --port <N> or --instance <N> to select another local runtime.

Viewer

A real-time web viewer at http://localhost:3113 shows memory building as sessions run, with authenticated SSE updates over the REST port. Useful for demos and for confirming capture is working.

agentmemory-architecture