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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Bounded local memory with CBDC authority gating: SQLite + FTS5 claims, scoped recall with explainable use/verify/ignore decisions and a full audit trail, /memory commands, ≤3-claim/1200-char injection per call, no extra model call.
dsh plugin --profile default add github:GIT121995/dsh-memory-gate -
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Memory Lake as a persistent memory layer for dsh: memory_search, memory_remember, and memory_forget tools over the memorylake CLI, a session status line, and guided setup/diagnostic skills, sharing one ~/.memorylake identity and memory set with the Claude Code and Codex plugins.
dsh plugin --profile default add github:memorylake-ai/memorylake-harness#path:/dsh-plugin -
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One shared Obsidian vault for every agent: dependency-free Python core (search/promote/adjudicate/forget), vault template, dsh plugin (memory_search/show/submit/status).
dsh plugin --profile default add github:Noelune/unified-agent-memory -
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Build auditable KB packs (SQLite FTS5) from md/txt/docx/pdf with deterministic retrieval and original-text reading.
dsh plugin --profile default add github:omdsh-dev/dsh-kb-sieve -
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Cited memory over DSH's lossless session log: distilled facts carry `(sessionId, eventRange)` citations that expand back to the exact original log excerpt.
dsh plugin --profile default add github:Jesse-njx/dsh-memory -
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Layered memory pipeline for DSH: auto-distills conversations into atomic facts, scene summaries and a persona profile (L0–L3), with hybrid BM25 + vector retrieval, chat/work family separation, and context injection before each model step.
dsh plugin --profile default add github:JunNanLYS/dsh-layered-memory
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.