Redis Agent Memory Server Model Card

这是可索引项目报告证据页：它保留 Redis Agent Memory Server Model Card 的源材料入口、机制线索和限制提醒；正文仍需 reader/editor 与 academic public-copy review 后才能当作最终结论引用。

Redis Agent Memory Server Model Card

1. Role in Self Evolve

agent-memory-server is Redis-maintained memory middleware that gives AI agents fast, persistent, and flexible context memory through an MCP-compatible service and client stack. It matters because self-evolving agents need explicit runtime, memory, skill, and benchmark substrates before their improvement claims become trustworthy.

2. Working Principle

capture agent events and context -> store and retrieve memory through Redis-backed services -> expose memory operations via MCP and client APIs -> feed retrieved context into later agent loops

3. Evidence Path

web-observed GitHub repo page and commit history showed 266 stars, 50 forks, 19 issues, 28 pull requests, 735 commits, MIT license, agent-memory-client plus MCP/server folders, and latest visible commits on 2026-04-16. This iteration keeps freshness honest: the snapshot comes from the public GitHub page observed on 2026-06-05, while shell GitHub API access remained blocked in this workspace.

4. Teaching Use

Use this card to explain Agent Memory Runtime and Context Service: it shows how swarm runtimes, skill optimizers, benchmark suites, browser harnesses, and memory middleware fit into the broader self-evolving-agent pipeline.

5. Limits

The repository was not cloned in this iteration; no benchmark run, workflow execution, or agent loop experiment was executed. Counts and claims are visible public-page signals unless independently revalidated later.