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leesgit

claude-session-continuity-mcp

by leesgit

memory_search

Search stored memories from previous sessions using keywords or semantic similarity. Filter by type, project, tags, and importance to quickly retrieve relevant context.

Instructions

Search stored memories using FTS5 full-text search or semantic/embedding similarity. Default mode returns compact index entries (id, type, truncated content) to save tokens — set detail=true for full content. Supports filtering by type, project, tags, and minimum importance. Read-only. Use memory_get to fetch full content for specific IDs found in search results. Use memory_related to explore graph connections from a known memory.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesNatural language search query
typeNoFilter by memory type (default: "all")
projectNoFilter by project (optional)
tagsNoFilter by tags — matches if any tag is present (optional)
semanticNoUse embedding-based semantic search instead of keyword FTS5 (default: false)
minImportanceNoMinimum importance threshold 1-10 (default: 1)
limitNoMax results to return (default: 10)
detailNoReturn full content per memory (default: false — returns compact index only)

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed8 schema fields changedv1.13.1
    • changedInput schema / properties / detail / description
      Previous value: -"true면 전체 content, false면 요약 인덱스만 (기본: false)"New value: +"Return full content per memory (default: false — returns compact index only)"
    • changedInput schema / properties / limit / description
      Previous value: -"결과 개수 (기본: 10)"New value: +"Max results to return (default: 10)"
    • changedInput schema / properties / minImportance / description
      Previous value: -"최소 중요도 (기본: 1)"New value: +"Minimum importance threshold 1-10 (default: 1)"
    • changedInput schema / properties / project / description
      Previous value: -"프로젝트 필터 (선택)"New value: +"Filter by project (optional)"
    • changedInput schema / properties / query / description
      Previous value: -"검색어 (자연어)"New value: +"Natural language search query"
    • changedInput schema / properties / semantic / description
      Previous value: -"시맨틱 검색 사용 (기본: false, 임베딩 기반)"New value: +"Use embedding-based semantic search instead of keyword FTS5 (default: false)"
    • changedInput schema / properties / tags / description
      Previous value: -"태그 필터 (선택)"New value: +"Filter by tags — matches if any tag is present (optional)"
    • changedInput schema / properties / type / description
      Previous value: -"메모리 타입 필터 (기본: all)"New value: +"Filter by memory type (default: \"all\")"
  2. First observedv1.13.0

TDQS

A4.2/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses that the tool is read-only, explains the default compact output vs. detailed mode, and describes the truncation of content. It does not mention response format fields but covers essential behaviors.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences. It front-loads the main purpose, then details default behavior and filtering, ending with sibling guidance. It is efficient and clear, though the second sentence could be slightly more structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 8 parameters (all documented in schema) and no output schema, the description adequately covers the purpose and usage. However, it does not specify the full output structure beyond 'id, type, truncated content', leaving some return fields unmentioned.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, so the baseline is 3. The description adds minimal new semantics beyond the schema, mostly listing filter options already present. It echoes schema descriptions for 'semantic' and 'detail' but does not introduce new meaning.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly specifies the verb 'search' and the resource 'stored memories', distinguishing it from siblings like memory_get and memory_related. It mentions both FTS5 keyword search and semantic embedding similarity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states when to use alternative tools: 'Use memory_get to fetch full content for specific IDs found in search results. Use memory_related to explore graph connections from a known memory.' It also clarifies the read-only nature.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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