agentscope-ai / agentscope-ai/agentscope-java

Could AgentScope Java support durable context across distributed agents?

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area/ext/memory enhancement
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Java
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Beschreibung

Hi, I’m Vivek Gupta, Founder & CEO at [MemCode](https://memcode.in). AgentScope Java is aimed at distributed, production-grade, long-running agents, where reliable context must survive service restarts, handoffs, and model changes. MemCode could provide an optional SOTA memory layer for approved user preferences, agent decisions, task knowledge, and cross-service handoffs.

The integration could scope memories by tenant, user, agent, workflow, or task; retrieve only relevant context at lifecycle boundaries; and preserve provenance with explicit inspection, correction, retention, export, and deletion. MemCode is available local/self-hosted—the engine/API runs in the operator’s Docker/VM or local process behind a private base URL, with records, embeddings, credentials, and logs kept inside that deployment. MCP and SDK support mean the first adapter or benchmark requires no core-code changes, while AgentScope Java remains authoritative for distributed execution and runtime state.

See the [MemCode Leviathan overview](https://memcode.in/leviathan). Would a Java SDK example, MCP connector, or focused benchmark be useful for the project? I’d be happy to open a small PR around the extension point you recommend.

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Rechercherichtung

The issue names no repository files, tests, or concrete extension point. First compare the proposed Java SDK example, MCP connector, and focused benchmark with AgentScope Java’s distributed execution and runtime-state boundaries. Done would require an agreed integration scope and a maintainer-approved implementation target.

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Bewertung

Tech-Stack
java
Bereich
ai, distributed-systems
Issue-Typ
Feature
Schwierigkeit
5/5
Geschätzter Aufwand
Über eine Woche
Aktivitätsstatus
Aktiv
Klarheit
Muss geklärt werden
Anfängerfreundlichkeit
25/100

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