46 lines
1.9 KiB
Markdown
46 lines
1.9 KiB
Markdown
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# Claude Memory MCP
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Persistent cross-session memory for Claude. Today it stores **Memories** as rows and
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retrieves them by **lexical recall** (full-text keyword matching). This context is being
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extended with **semantic recall** (embeddings) and a **concept graph** so retrieval works
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by meaning and related memories become traversable.
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## Language
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**Memory**:
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A single stored unit of knowledge — a fact, preference, decision, project note, or person
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detail — with content plus metadata (category, tags, importance). The atomic thing a user
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stores and recalls.
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**Recall**:
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Retrieving the Memories most relevant to a query. The read path.
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**Lexical recall**:
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The existing retrieval method — matches Memories whose words (content, tags, LLM-generated
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keywords) overlap the query, ranked by BM25 / `ts_rank`. Matches *tokens*, not meaning.
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_Avoid_: calling this "semantic search" — it is not semantic.
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**Semantic recall**:
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Retrieval by meaning via dense-vector **Embedding** similarity, so a query surfaces a Memory
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even with zero shared words (e.g. "what UI library?" → "prefers Svelte").
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**Embedding**:
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A dense vector representation of a Memory's (or Concept's) meaning, used for Semantic recall.
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**Concept**:
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A distinct entity or idea that recurs across Memories (e.g. "Svelte", "Viktor", "TripIt",
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"frontend framework"). A node in the Concept graph. Distinct from a Memory: one Memory can
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mention several Concepts, and one Concept spans many Memories.
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**Concept graph**:
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The network of Concepts joined by typed **Relationships**, making the memory store
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traversable — from one Memory or Concept to related ones.
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**Relationship**:
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A typed, directed edge in the Concept graph, between two Concepts or between a Memory and a
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Concept (e.g. `prefers`, `is-a`, `used-in`, `mentions`).
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**Hybrid retrieval**:
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The target read path — combining Lexical recall, Semantic recall, and Concept-graph
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traversal into one ranked result set.
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