Memory & Context Plugins Memory & Context
75 plugins
Plugins that give your agent long-term memory, knowledge persistence, and context management. From simple key-value stores to full knowledge graphs with vector search.
75 plugins
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Tracks the agent's state as Yogācāra mental factors over a durable seed store, and feeds it back into the prompt as first-person inclination.
dsh plugin --profile default add github:tancheng33/dsh-yogacara -
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Bi-temporal memory backed by a SodaMem daemon: recall is contributed to the prompt while each turn is assembled and every closed turn is ingested, with no tool call and no model call on the read path; each recalled fact cites the turn it came from and carries validity dates, so superseded facts stop being retrieved.
dsh plugin --profile default add github:SodaMem/dsh-plugin-sodamem -
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DSH ↔ agentmemory session-memory bridge: mirrors session lifecycle into a local agentmemory daemon (REST), exposes memory_recall / memory_remember tools, and injects a per-session memory context window via agent/pre-step.
dsh plugin --profile default add github:Yiipu/dsh-agentmemory -
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Focus board for DeepSeek Harness agents: durable, model-maintained notes in the session workspace that pin the objective, constraints, and decisions across compaction and sessions, with automatic context injection, archive on clear, and an optional web panel.
dsh plugin --profile default add github:863683348/dsh-plugin-focus -
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Session context triage for long DeepSeek Harness sessions: deterministic screeners trim stale, duplicate, failed, and oversized content through the official ctx.compaction seam.
dsh plugin --profile default add github:JohnXu22786/context-pruner -
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Connect Trilium notes to the DSH agent via ETAPI with 20 agent tools: durable memory (remember/recall + auto-injected index), note management (CRUD/clone/attributes/revisions), full-text search, weekly-report workflow, attachments, calendar notes, backup/import, and a settings card.
dsh plugin --profile default add github:MineRPi/dsh-trilium
Frequently Asked QuestionsFAQ
Memory plugins store knowledge that persists across multiple sessions — facts, entities, and conversation summaries. Session plugins manage the current conversation's state: message history, branching, and import/export.
Most memory plugins add 50-200ms per turn for retrieval. Vector-search plugins are slightly slower but much better at finding relevant context. Key-value stores are fastest.
Yes. A common pattern is context-compression for the current session plus a vector-recall plugin for long-term knowledge.