Complete parameter reference for all three search endpoints: document search, memory search, and execute search.

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Common Parameters

These parameters work across all search endpoints:
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q
string
required
Search query stringThe text you want to search for. Can be natural language, keywords, or questions.
q: "machine learning neural networks"
q: "What are the applications of quantum computing?"
q: "python tutorial beginner"
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limit
number
default:"10"
Maximum number of results to returnControls how many results you get back. Higher limits increase response time and size.
limit: 5    // Fast, focused results
limit: 20   // Comprehensive results
limit: 100  // Maximum recommended
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containerTags
Array<string>
Filter by container tagsOrganizational tags for filtering results. Uses exact array matching - must match all tags in the same order.
containerTags: ["user_123"]                    // Single tag
containerTags: ["user_123", "project_ai"]      // Multiple tags (exact match)
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filters
string
Metadata filtering with SQL-like structureJSON string containing AND/OR logic for filtering by metadata fields. Uses the same structure as memory listing filters.
filters: JSON.stringify({
  AND: [
    { key: "category", value: "tutorial", negate: false },
    { key: "difficulty", value: "beginner", negate: false }
  ]
})
See Metadata Filtering Guide for complete syntax and examples.
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rerank
boolean
default:"false"
Re-score results for better relevanceApplies a secondary ranking algorithm to improve result quality. Adds ~100-200ms latency but increases accuracy.
rerank: true   // Better accuracy, slower
rerank: false  // Faster, standard accuracy
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rewriteQuery
boolean
default:"false"
Expand and improve the queryRewrites your query to find more relevant results. Particularly useful for abbreviations and domain-specific terms. Adds ~400ms latency.
// Query rewriting examples:
"ML" → "machine learning artificial intelligence"
"JS" → "JavaScript programming language"
"API" → "application programming interface REST"
Query rewriting significantly increases latency. Only use when search quality is more important than speed.

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Document Search Parameters (POST /v3/search)

These parameters are specific to client.search.documents():
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chunkThreshold
number
default:"0.5"
Sensitivity for chunk selectionControls which text chunks are included in results:
  • 0.0 = Least sensitive (more chunks, more results)
  • 1.0 = Most sensitive (fewer chunks, higher quality)
chunkThreshold: 0.2   // Broad search, many chunks
chunkThreshold: 0.8   // Precise search, only relevant chunks
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documentThreshold
number
default:"0.5"
Sensitivity for document selectionControls which documents are considered for search:
  • 0.0 = Search more documents (comprehensive)
  • 1.0 = Search only highly relevant documents (focused)
documentThreshold: 0.1   // Cast wide net
documentThreshold: 0.9   // Only very relevant documents
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docId
string
Search within a specific documentLimit search to chunks within a single document. Useful for finding content in large documents.
docId: "doc_abc123"  // Only search this document
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onlyMatchingChunks
boolean
default:"false"
Return only exact matching chunksBy default, Supermemory includes surrounding chunks for context. Set to true to get only the exact matching text.
onlyMatchingChunks: false  // Include context chunks (default)
onlyMatchingChunks: true   // Only matching chunks
Context chunks help LLMs understand the full meaning. Only disable if you need precise text extraction.
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includeFullDocs
boolean
default:"false"
Include complete document contentAdds the full document text to each result. Useful for chatbots that need complete context.
includeFullDocs: true   // Full document in response
includeFullDocs: false  // Only chunks and metadata
Including full documents can make responses very large. Use sparingly and with appropriate limits.
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includeSummary
boolean
default:"false"
Include document summariesAdds AI-generated document summaries to results. Good middle-ground between chunks and full documents.
includeSummary: true   // Include document summaries
includeSummary: false  // No summaries
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filters
string
Filter by metadata using SQL queries

// Use this instead:
filters: JSON.stringify({
  OR: [
    { key: "category", value: "technology", negate: false },
    { key: "category", value: "science", negate: false }
  ]
})

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Memory Search Parameters (POST /v4/search)

These parameters are specific to client.search.memories():
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threshold
number
default:"0.5"
Sensitivity for memory selectionControls which memories are returned based on similarity:
  • 0.0 = Return more memories (broad search)
  • 1.0 = Return only highly similar memories (precise search)
threshold: 0.3   // Broader memory search
threshold: 0.8   // Only very similar memories
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containerTag
string
Filter by single container tagNote: Memory search uses containerTag (singular) while document search uses containerTags (plural array).
containerTag: "user_123"  // Single tag for memory search
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include
object
Control what additional data to includeObject specifying what contextual information to include with memory results.
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include.documents
boolean
default:"false"
Include associated documents for each memory
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include.relatedMemories
boolean
default:"false"
Include parent and child memories (contextual relationships)
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include.summaries
boolean
default:"false"
Include memory summaries
include: {
  documents: true,        // Show related documents
  relatedMemories: true,  // Show parent/child memories
  summaries: true         // Include summaries
}