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Copy file name to clipboardExpand all lines: docs/cli/me-memory.md
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| Argument | Required | Description |
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|----------|----------|-------------|
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|`query`| no |Semantic search query (shorthand for `--semantic`). |
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|`query`| no |Hybrid search query (uses both semantic and fulltext search). |
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| Option | Description |
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|--------|-------------|
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|`--weight-fulltext <w>`| Fulltext weight, 0-1. |
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|`--order-by <dir>`| Sort direction: `asc` or `desc`. |
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At least one search criterion is required. When both `--semantic`and `--fulltext`are provided, results are ranked using Reciprocal Rank Fusion (hybrid mode).
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At least one search criterion is required. A positional `query` runs hybrid search by sending the same text to semantic and fulltext ranking. Use `--semantic`for pure vector search, `--fulltext`for pure keyword search, or both flags to provide different text for each mode.
Find memories by meaning. Uses vector embeddings and cosine similarity.
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```bash
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me memory search "how does authentication work"
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me memory search --semantic "how does authentication work"
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```
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Good for finding conceptually related content even when the exact words differ.
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Good for finding conceptually related content even when the exact words differ. For short literal terms, identifiers, and exact words, prefer fulltext or hybrid search; semantic-only rankings are not lexical and can return unrelated short memories.
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### Fulltext search
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Combine both modes. Results are ranked using Reciprocal Rank Fusion (RRF), which merges the two ranked lists into a single result set.
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```bash
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me memory search "embedding performance"
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# or provide different text for each ranker:
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me memory search --semantic "embedding performance" --fulltext "nomic ollama"
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```
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Good when you want both meaning-based and keyword-based relevance.
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Good when you want both meaning-based and keyword-based relevance. The positional CLI query uses hybrid search and is the recommended default.
Copy file name to clipboardExpand all lines: docs/mcp/me_memory_search.md
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Search and browse memories using text matching and/or filters.
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Supports three search modes: **semantic** (meaning-based), **fulltext** (keyword-based via BM25), or **hybrid** (both combined via Reciprocal Rank Fusion). Combine any search mode with tree, meta, and temporal filters.
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Supports three search modes: **semantic** (meaning-based), **fulltext** (keyword-based via BM25), or **hybrid** (both combined via Reciprocal Rank Fusion). Combine any search mode with tree, meta, and temporal filters. For ordinary user queries, short terms, identifiers, or exact words, prefer hybrid by setting both `semantic` and `fulltext` to the query text.
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## Parameters
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```json
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{
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"semantic": "how does authentication work",
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"limit": 10,
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"semanticThreshold": 0.7
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"limit": 10
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}
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```
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### Hybrid search (recommended default)
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```json
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{
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"semantic": "panics",
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"fulltext": "panics",
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"limit": 10
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}
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```
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- Provide at least one of `semantic`, `fulltext`, or a filter (`tree`, `meta`, `temporal`, `grep`) -- otherwise the search has no criteria.
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- Optional parameters may be omitted or explicitly passed as `null` — both are treated as "no value".
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- When both `semantic` and `fulltext` are provided, results are ranked using Reciprocal Rank Fusion (hybrid mode).
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- When both `semantic` and `fulltext` are provided, results are ranked using Reciprocal Rank Fusion (hybrid mode). This is recommended for single-word or literal searches because semantic-only ranking does not guarantee exact-word matches rank first.
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-`order_by` only applies to filter-only searches (no `semantic`/`fulltext`). Ranked searches are always sorted by score.
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-`score` ranges from 0 to 1, where 1 is the best match.
description: `Search and browse memories using text matching and/or filters.
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Search modes: semantic (meaning), fulltext (keywords), or both (hybrid). Combine with tree, meta, and temporal filters. Results scored 0-1.
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Search modes: semantic (meaning), fulltext (keywords), or both (hybrid). For ordinary queries, short terms, identifiers, or exact words, prefer hybrid by setting both semantic and fulltext to the query text. Combine with tree, meta, and temporal filters. Results scored 0-1.
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Docs: ${docUrl("me_memory_search")}`,
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inputSchema: {
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semantic: z
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.string()
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.optional()
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.nullable()
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.describe("Natural language query for semantic/meaning search"),
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.describe(
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"Natural language query for semantic/meaning search. For short or literal queries, also set fulltext to the same value.",
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