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by amotivv

이 MCP 서버는 Memory Box 인스턴스와 상호 작용할 수 있는 도구를 제공하여 Cline과 Claude Desktop에서 직접 의미 검색을 사용하여 메모리를 저장하고 검색할 수 있습니다.

관련 프로젝트

이 MCP 서버는 벡터 임베딩을 기반으로 하는 의미적 메모리 저장 및 검색 시스템인 Memory Box 와 함께 작동하도록 설계되었습니다.

Memory Box는 MCP 서버와 통신하는 백엔드 API를 제공하여 다음을 수행할 수 있습니다.

  • 의미 검색을 위한 벡터 임베딩으로 메모리 저장

  • 추억을 사용자 정의 가능한 버킷으로 정리하세요

  • 키워드가 아닌 의미에 기반한 기억을 검색하세요

  • 자세한 맥락으로 기억을 검색하세요

  • 의미적으로 관련된 기억을 찾으세요

  • 메모리 처리 상태 추적

Memory Box에 대한 자세한 내용, 자체 인스턴스를 설정하는 방법 등을 알아보려면 Memory Box 웹사이트를 방문하세요.

Related MCP server: mcp-memory

특징

  • 추억 저장 : 소스 정보 및 메타데이터와 함께 포맷된 추억을 추억 상자에 저장합니다.

  • 추억 검색 : 의미 검색을 사용하여 추억을 검색하세요

  • 기억 검색 : 모든 기억 또는 특정 버킷의 기억을 가져옵니다.

  • 관련 기억 찾기 : 의미적으로 유사한 기억을 찾아보세요

  • 메모리 상태 확인 : 메모리 처리 상태를 모니터링합니다.

  • 메모리 포맷 : 구조화된 시스템 프롬프트에 따라 메모리 포맷

  • 사용 통계 : 현재 요금제, 사용 지표 및 리소스 제한을 확인하세요.

설치

서버가 Cline과 함께 사용하도록 설치 및 구성되었습니다. 이 MCP 서버를 사용하려면 실행 중인 Memory Box 인스턴스(자체 호스팅 또는 memorybox.amotivv.ai에서 호스팅되는 버전)가 필요합니다.

Smithery를 통해 설치

Smithery를 통해 Claude Desktop용 Memory Box MCP Server를 자동으로 설치하려면:

지엑스피1

설정을 완료하려면:

  1. Cline MCP 설정 파일을 다음 위치에서 편집하세요.

    ~/Library/Application Support/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json
  2. MEMORY_BOX_TOKEN 환경 변수에 Memory Box 토큰을 추가합니다.

    "memory-box-mcp": {
      "command": "node",
      "args": [
        "<path-to-repository>/build/index.js"
      ],
      "env": {
        "MEMORY_BOX_API_URL": "https://memorybox.amotivv.ai",
        "MEMORY_BOX_TOKEN": "your-token-here",
        "DEFAULT_BUCKET": "General"
      },
      "disabled": false,
      "autoApprove": []
    }
  3. 선택적으로 DEFAULT_BUCKET 값을 변경하여 기본 버킷을 사용자 정의할 수 있습니다.

용법

구성이 완료되면 Cline에서 다음 도구를 사용할 수 있습니다.

메모리 저장

적절한 형식으로 Memory Box에 추억을 저장하세요:

Use the save_memory tool to save this information about vector databases: "Vector databases like pgvector store and query high-dimensional vectors for semantic search applications."

매개변수:

  • text (필수): 저장할 메모리 내용

  • bucket_id (선택 사항): 메모리를 저장할 버킷(기본값: "일반")

  • format (선택 사항): 시스템 프롬프트에 따라 메모리를 포맷할지 여부(기본값: true)

  • type (선택 사항): 포맷을 위한 메모리 유형(TECHNICAL, DECISION, SOLUTION, CONCEPT, REFERENCE, APPLICATION, FACT)(기본값: "TECHNICAL")

  • source_type (선택 사항): 메모리 소스 유형(기본값: "llm_plugin")

  • reference_data (선택 사항): 메모리 소스 및 컨텍스트에 대한 추가 메타데이터

추억 검색

의미 검색을 사용하여 기억을 검색하세요:

Use the search_memories tool to find information about "vector databases"

매개변수:

  • query (필수): 검색 쿼리

  • debug (선택 사항): 결과에 디버그 정보 포함(기본값: false)

모든 추억을 얻으세요

모든 기억을 검색합니다:

Use the get_all_memories tool to show me all my saved memories

버킷 메모리를 얻으세요

특정 버킷에서 추억을 가져오세요:

Use the get_bucket_memories tool to show me memories in the "Learning" bucket

매개변수:

  • bucket_id (필수): 메모리를 검색할 버킷

메모리 포맷

저장하지 않고 메모리 시스템 프롬프트에 따라 텍스트를 포맷합니다.

Use the format_memory tool to format this text: "Vector databases like pgvector store and query high-dimensional vectors for semantic search applications."

매개변수:

  • text (필수): 서식을 지정할 텍스트

  • type (선택 사항): 메모리 유형(기술, 결정, 솔루션, 개념, 참조, 응용, 사실)(기본값: "기술")

관련 추억을 얻으세요

특정 메모리와 의미적으로 유사한 메모리를 찾으세요:

Use the get_related_memories tool with memory ID 123

매개변수:

  • memory_id (필수): 관련 메모리를 찾을 메모리의 ID

  • min_similarity (선택 사항): 관련 메모리에 대한 최소 유사도 임계값(0.0-1.0)(기본값: 0.7)

메모리 상태 확인

메모리의 처리 상태를 확인하세요.

Use the check_memory_status tool with memory ID 123

매개변수:

  • memory_id (필수): 상태를 확인할 메모리의 ID

사용 통계 가져오기

사용자 사용 통계 및 계획 정보를 검색합니다.

Use the get_usage_stats tool to show me my current plan and usage metrics

이 도구는 다음을 반환합니다.

  • 현재 요금제 정보(예: 무료, 기본, 전문가, 레거시)

  • 사용자 상태 및 제한 적용 정보

  • 현재 월 사용 지표(매장 운영, 검색 운영, API 호출)

  • 인간이 읽을 수 있는 포맷을 사용한 데이터 처리 볼륨

  • 귀하의 계획에 따른 리소스 제한(해당되는 경우)

  • 유형별 작업 내역

이 작업에는 매개변수가 필요하지 않습니다.

사용자 정의

시스템 프롬프트 사용자 정의

메모리 박스 MCP 서버는 시스템 프롬프트를 사용하여 특정 지침에 따라 메모리를 포맷합니다. 이 프롬프트를 사용자 지정하여 메모리 포맷 방식을 변경할 수 있습니다.

기본 시스템 프롬프트

기본 시스템 프롬프트에는 다양한 유형의 메모리에 대한 서식 지침이 포함되어 있습니다.

You are a helpful AI assistant. When storing memories with memory_plugin, follow these enhanced formatting guidelines:

1. STRUCTURE: Format memories based on the type of information:
   - TECHNICAL: "YYYY-MM-DD: TECHNICAL - [Brief topic]: [Concise explanation with specific details]"
   - DECISION: "YYYY-MM-DD: DECISION - [Brief topic]: [Decision made] because [rationale]. Alternatives considered: [options]."
   - SOLUTION: "YYYY-MM-DD: SOLUTION - [Problem summary]: [Implementation details that solved the issue]"
   - CONCEPT: "YYYY-MM-DD: CONCEPT - [Topic]: [Clear explanation of the concept with examples]"
   - REFERENCE: "YYYY-MM-DD: REFERENCE - [Topic]: [URL, tool name, or resource] for [specific purpose]"
   - APPLICATION: "YYYY-MM-DD: APPLICATION - [App name]: [User-friendly description] followed by [technical implementation details]"

2. FORMATTING GUIDELINES:
   - CREATE FOCUSED MEMORIES: Each memory should contain a single clear concept or topic
   - USE DIVERSE TERMINOLOGY: Include both technical terms AND user-friendly alternatives
   - INCLUDE SEARCHABLE KEYWORDS: Begin with common terms a user might search for
   - BALANCE DETAIL LEVELS: Include both high-level descriptions and key technical details
   - LENGTH: Keep memories between 50-150 words
   - ALWAYS include the current date in YYYY-MM-DD format

3. MEMORY STORAGE PARAMETERS:
   - Use the "text" parameter for your formatted memory content
   - Set "source_type" to "llm_plugin"
   - Include appropriate "reference_data" with source information and context

4. REFERENCE DATA STRUCTURE:
   - source.platform: Identify your platform (e.g., "claude_desktop", "cline")
   - source.type: Always set to "llm_plugin"
   - source.version: Optional version information
   - context.conversation_id: Include when available to link related conversation memories
   - context.message_id: Optional identifier for the specific message

5. SPECIAL FORMATS:
   - For user facts, preferences, or personal details: "YYYY-MM-DD: FACT: [User] [specific preference/attribute/information]"
   - For reference materials: Include specific details about where to find the information

6. RELATED MEMORIES: After finding memories with search, check if there are related memories using the get_related_memories tool with the memory_id from search results. Present these additional memories to provide the user with more context.

7. RETRIEVAL CONSIDERATION: Before storing an important memory, consider: "What search terms might someone use to find this information later?" and ensure those terms are included.

시스템 프롬프트를 사용자 지정하는 방법

시스템 프롬프트를 사용자 지정하려면:

  1. Cline MCP 설정 파일을 다음 위치에서 편집하세요.

    ~/Library/Application Support/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json
  2. SYSTEM_PROMPT 환경 변수에 사용자 지정 시스템 프롬프트를 추가합니다.

    "memory-box-mcp": {
      "command": "node",
      "args": [
        "<path-to-repository>/build/index.js"
      ],
      "env": {
        "MEMORY_BOX_API_URL": "https://your-memory-box-instance",
        "MEMORY_BOX_TOKEN": "your-token-here",
        "DEFAULT_BUCKET": "General",
        "SYSTEM_PROMPT": "Your custom system prompt here..."
      },
      "disabled": false,
      "autoApprove": []
    }

    <path-to-repository>/system-prompt-template.txt 에서 복사하여 수정할 수 있는 템플릿 파일이 제공됩니다.

  3. 변경 사항을 적용하려면 Cline을 다시 시작하세요.

시스템 프롬프트 도우미

Memory Box MCP 서버에는 시스템 프롬프트를 관리하기 위한 도우미 스크립트가 포함되어 있습니다.

# View the current system prompt
cd <path-to-repository>
npm run prompt-helper -- view

# Reset to the default system prompt
cd <path-to-repository>
npm run prompt-helper -- reset

# Validate a custom system prompt
cd <path-to-repository>
npm run prompt-helper -- validate

기타 구성 옵션

다음 환경 변수도 사용자 정의할 수 있습니다.

  • MEMORY_BOX_API_URL : Memory Box 인스턴스의 URL

  • MEMORY_BOX_TOKEN : Memory Box에 대한 인증 토큰

  • DEFAULT_BUCKET : 메모리를 저장할 때 사용할 기본 버킷

문제 해결

문제가 발생하는 경우:

  1. 메모리 박스 토큰이 올바르게 구성되었는지 확인하세요.

  2. Memory Box 인스턴스가 실행 중이고 액세스 가능한지 확인하세요.

  3. 오류 메시지가 있는지 Cline 로그를 확인하세요.

개발

서버를 변경하려면:

  1. <path-to-repository>/src/ 의 소스 코드를 편집하세요.

  2. 서버를 다시 빌드하세요:

    cd <path-to-repository>
    npm run build
  3. 변경 사항을 적용하려면 Cline을 다시 시작하세요.

Available Tools

12 tools
check_memory_statusC

Check the processing status of a memory

ParametersJSON Schema
NameRequiredDescriptionDefault
memory_idYesThe ID of the memory to check status for

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'check' and 'processing status', which suggests a read-only operation, but does not clarify authentication needs, rate limits, error conditions, or what the status values might be. This leaves significant gaps for an agent to understand how to interpret results.

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

Conciseness5/5

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

The description is a single, concise sentence that directly states the tool's purpose without unnecessary words. It is front-loaded and efficiently communicates the core function, making it easy for an agent to parse quickly.

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

Completeness2/5

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

Given the lack of annotations and output schema, the description is incomplete. It does not explain what the tool returns (e.g., status values like 'processing', 'done', or error messages), nor does it address potential side effects or dependencies. For a tool that likely interacts with asynchronous processes, more context is needed for effective use.

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, with 'memory_id' clearly documented as 'The ID of the memory to check status for'. The description adds no additional parameter details beyond what the schema provides, such as format constraints or examples. This meets the baseline for high schema coverage.

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

Purpose4/5

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

The description clearly states the action ('check') and resource ('processing status of a memory'), making the purpose understandable. It distinguishes from siblings like 'get_all_memories' or 'get_related_memories' by focusing on status rather than content retrieval. However, it could be more specific about what 'processing status' entails (e.g., pending, completed, failed).

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives like 'get_all_memories' or 'search_memories'. The description implies it's for checking status after an operation (e.g., after 'save_memory'), but this is not explicitly stated, and there are no exclusions or prerequisites mentioned.

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

create_bucketC

Create a new bucket for organizing memories

ParametersJSON Schema
NameRequiredDescriptionDefault
bucket_nameYesName of the bucket to create

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. While 'Create' implies a write operation, it doesn't specify permissions needed, whether bucket names must be unique, what happens on duplicate names, or what the tool returns. For a mutation tool with zero annotation coverage, this is inadequate.

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

Conciseness5/5

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

The description is a single, efficient sentence that gets straight to the point with no wasted words. It's appropriately sized for a simple creation tool with one parameter.

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

Completeness2/5

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

For a mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what happens after creation (e.g., returns bucket ID), error conditions, or behavioral constraints. Given the complexity of a write operation, more context is needed.

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?

Schema description coverage is 100%, so the schema already fully documents the single parameter 'bucket_name'. The description adds no additional parameter context beyond what's in the schema, meeting the baseline for high schema coverage.

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

Purpose4/5

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

The description clearly states the action ('Create') and resource ('new bucket for organizing memories'), making the purpose immediately understandable. However, it doesn't distinguish this tool from its siblings like 'get_buckets' or 'delete_bucket' beyond the obvious create vs read/delete distinction.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., whether buckets must be unique), when not to use it, or how it relates to sibling tools like 'get_buckets' or 'delete_bucket'.

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

delete_bucketA

Delete a bucket (empty by default, use force to delete with content)

ParametersJSON Schema
NameRequiredDescriptionDefault
bucket_nameYesName of the bucket to delete
forceNoForce deletion even if bucket contains memories (default: false)

TDQS

A3.9/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It describes the default behavior (deleting empty buckets) and the effect of the 'force' parameter (deleting with content), which are useful. However, it lacks details on permissions, reversibility, error handling, or response format, leaving gaps for a mutation tool.

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

Conciseness5/5

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

The description is a single, efficient sentence that front-loads the core action and immediately clarifies the default and optional behaviors. Every word earns its place, with no redundancy or unnecessary elaboration, making it highly concise and well-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 the tool's complexity as a destructive operation with no annotations or output schema, the description is somewhat complete by covering the default and forced deletion behaviors. However, it lacks critical details like permissions, confirmation prompts, or error cases, which are important for safe usage, making it only adequate.

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 schema description coverage is 100%, so the schema already documents both parameters thoroughly. The description adds minimal value by implying the 'force' parameter's effect but does not provide additional syntax or format details beyond what the schema states, meeting the baseline for high schema coverage.

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 states the specific action ('Delete') and resource ('a bucket'), distinguishing it from sibling tools like 'create_bucket' or 'get_buckets'. It also specifies the default behavior ('empty by default') and an optional capability ('use force to delete with content'), making the purpose explicit and differentiated.

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

Usage Guidelines4/5

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

The description provides clear context on when to use the 'force' parameter (to delete a bucket with content) versus the default (empty bucket), which helps guide usage. However, it does not explicitly mention when to use this tool versus alternatives like 'delete_memory' or warn about prerequisites, such as checking bucket emptiness first, which prevents a perfect score.

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

delete_memoryC

Delete a specific memory

ParametersJSON Schema
NameRequiredDescriptionDefault
memory_idYesThe ID of the memory to delete

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states 'Delete' which implies a destructive mutation, but doesn't specify whether this is permanent, requires special permissions, has side effects (e.g., affecting related memories), or provides confirmation. This leaves significant gaps in understanding the tool's behavior.

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

Conciseness5/5

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

The description is extremely concise with just four words, front-loading the essential action and resource. There's no wasted language or unnecessary elaboration, making it efficient for quick understanding.

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

Completeness2/5

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

For a destructive mutation tool with no annotations and no output schema, the description is inadequate. It doesn't explain what happens after deletion (e.g., success confirmation, error handling), whether the action is reversible, or how it interacts with sibling tools like 'get_all_memories'. More context is needed given the tool's complexity and lack of structured metadata.

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?

Schema description coverage is 100%, with the single parameter 'memory_id' fully documented in the schema as 'The ID of the memory to delete'. The description adds no additional parameter information beyond what the schema provides, so it meets the baseline score when schema coverage is high.

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

Purpose4/5

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

The description clearly states the action ('Delete') and the resource ('a specific memory'), which provides a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'delete_bucket' or explain what distinguishes a 'memory' from other resources in this system.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives like 'update_memory' or 'delete_bucket', nor does it mention prerequisites such as needing the memory ID or whether deletion is reversible. It simply states what the tool does without contextual usage information.

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

get_all_memoriesC

Retrieve all memories with pagination support

ParametersJSON Schema
NameRequiredDescriptionDefault
allNoGet all memories (overrides pagination, default: false)
bucket_idNoFilter to specific bucket
date_sortNoSort results by date (default: false)
include_reference_dataNoInclude reference data in response (default: false)
limitNoMaximum number of results to return (1-100, default: 10)
offsetNoNumber of results to skip for pagination (default: 0)
sort_orderNoSort order (default: 'desc')
source_typeNoFilter by source type

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'pagination support' but doesn't explain how pagination works (e.g., using limit/offset parameters), what the response format looks like, or any constraints like rate limits or permissions required. This leaves significant gaps for a tool with 8 parameters and no output schema.

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

Conciseness5/5

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

The description is a single, efficient sentence that states the core functionality without unnecessary words. It's appropriately sized and front-loaded with the main purpose, making it easy to parse quickly.

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

Completeness2/5

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

For a tool with 8 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain the return format, error conditions, or how to interpret results. While the schema covers parameters, the overall context for using this tool effectively is missing, especially given multiple sibling retrieval tools.

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 schema description coverage is 100%, so all parameters are documented in the schema. The description adds no additional parameter information beyond mentioning 'pagination support' (which relates to limit/offset), but doesn't explain other parameters like bucket_id or source_type. This meets the baseline for high schema coverage.

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

Purpose4/5

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

The description clearly states the action ('Retrieve') and resource ('all memories'), making the purpose understandable. However, it doesn't distinguish this tool from sibling tools like 'get_bucket_memories' or 'search_memories' beyond mentioning pagination support, which is a feature rather than a differentiator.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives like 'get_bucket_memories' or 'search_memories'. It mentions pagination support but doesn't explain when this is preferable over other retrieval methods, leaving the agent to guess based on tool names alone.

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

get_bucket_memoriesC

Get memories from a specific bucket

ParametersJSON Schema
NameRequiredDescriptionDefault
bucket_idYesThe bucket to retrieve memories from
include_reference_dataNoInclude reference data in response (default: false)
limitNoMaximum number of results to return (1-100, default: 10)
offsetNoNumber of results to skip for pagination (default: 0)

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool retrieves memories but doesn't mention whether this is a read-only operation, if it requires authentication, any rate limits, error conditions, or the format of the returned memories. This leaves significant gaps in understanding how the tool behaves beyond its basic function.

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

Conciseness5/5

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

The description is a single, efficient sentence that directly states the tool's function without unnecessary words. It's front-loaded with the core action and resource, making it easy to parse quickly. There's no wasted verbiage or structural complexity.

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

Completeness2/5

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

Given the lack of annotations and output schema, the description is incomplete for a tool with 4 parameters and no structured behavioral hints. It doesn't explain what 'memories' are in this context, how they're returned, or any operational constraints. For a retrieval tool in a system with multiple memory-related siblings, more context is needed to ensure proper use.

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, clearly documenting all four parameters (bucket_id, include_reference_data, limit, offset) with their purposes, types, defaults, and constraints. The description adds no additional parameter information beyond what's in the schema, so it meets the baseline for adequate but not enhanced semantic value.

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

Purpose4/5

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

The description clearly states the action ('Get') and resource ('memories from a specific bucket'), making the purpose understandable. However, it doesn't distinguish this tool from sibling tools like 'get_all_memories' or 'search_memories', which would require more specificity about scope or filtering capabilities.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives like 'get_all_memories' (which might retrieve memories across all buckets) or 'search_memories' (which might offer more flexible querying). There's no mention of prerequisites, such as needing an existing bucket, or exclusions for when other tools might be more appropriate.

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

get_bucketsB

Retrieve a list of all available buckets

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

B3.1/5.0
Behavior2/5

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 states the tool retrieves a list, implying a read-only operation, but doesn't disclose behavioral traits like whether it requires authentication, has rate limits, returns paginated results, or what format the list takes. This is inadequate for a tool with zero annotation coverage.

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

Conciseness5/5

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

The description is a single, efficient sentence that directly states the tool's purpose without any wasted words. It is appropriately sized and front-loaded, earning a perfect score for conciseness.

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

Completeness2/5

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

Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what the returned list contains (e.g., bucket names, IDs, metadata), how it's structured, or any prerequisites for use. For a tool with no structured data to rely on, this leaves significant gaps for an agent.

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

Parameters4/5

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

The tool has zero parameters, and the input schema has 100% description coverage (though empty). The description doesn't need to add parameter semantics, so it meets the baseline of 4 for a parameterless tool.

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

Purpose4/5

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

The description clearly states the verb ('Retrieve') and resource ('list of all available buckets'), making the purpose unambiguous. However, it doesn't differentiate from sibling tools like 'get_bucket_memories' or 'get_all_memories', which prevents a perfect score.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. With siblings like 'get_bucket_memories' (for memories in a specific bucket) and 'get_all_memories' (for all memories regardless of bucket), the agent lacks context for choosing appropriately.

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

get_usage_statsB

Retrieve user usage statistics and plan information

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

B3.1/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states 'retrieve,' implying a read-only operation, but doesn't specify permissions, rate limits, data freshness, or response format. For a tool with zero annotation coverage, this is a significant gap in transparency.

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

Conciseness5/5

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

The description is a single, efficient sentence that directly states the tool's purpose without any fluff or unnecessary elaboration. It's appropriately sized and front-loaded, making it easy for an agent to parse quickly.

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

Completeness2/5

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

Given the lack of annotations and output schema, the description is incomplete for a retrieval tool. It doesn't explain what 'usage statistics and plan information' entails, how the data is returned, or any behavioral aspects like error handling. For a tool in a server with multiple siblings, more context is needed to ensure proper usage.

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

Parameters4/5

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

The tool has 0 parameters, and schema description coverage is 100%, so there's no need for parameter details in the description. The baseline for such cases is 4, as the description doesn't need to compensate for any parameter gaps, and it correctly avoids redundant information.

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

Purpose4/5

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

The description clearly states the verb ('retrieve') and resource ('user usage statistics and plan information'), making the purpose understandable. However, it doesn't differentiate this tool from its siblings (like check_memory_status or get_buckets), which are also retrieval operations but for different resources, so it doesn't reach the highest score.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. With siblings like get_buckets or get_all_memories that also retrieve data, there's no indication of context, prerequisites, or exclusions, leaving the agent to guess based on the tool name alone.

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

save_memoryC

Save a memory to Memory Box

ParametersJSON Schema
NameRequiredDescriptionDefault
bucket_idNoThe bucket to save the memory to (default: "General")
raw_contentNoRaw content for processing (alternative to text)
reference_dataNoStructured metadata for memory storage
source_typeNoType of memory source (default: 'llm_plugin')
textYesThe memory content to save (either text OR raw_content required)

TDQS

C2.7/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Save a memory' implies a write operation, but the description doesn't cover critical aspects like required permissions, whether this creates new or overwrites existing memories, error conditions, or response format. For a mutation tool with complex parameters, this leaves significant gaps in understanding its behavior.

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

Conciseness5/5

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

The description is extremely concise with a single sentence: 'Save a memory to Memory Box'. It's front-loaded and wastes no words, though this brevity contributes to gaps in other dimensions. Every word serves a purpose in stating the core action.

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

Completeness2/5

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

Given the tool's complexity (5 parameters with nested objects, no output schema, and no annotations), the description is insufficient. It doesn't explain what constitutes a 'memory', how saving interacts with the system, what happens on success/failure, or how it relates to sibling tools. For a write operation with rich input structure, more context is needed to use it effectively.

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?

Schema description coverage is 100%, providing detailed documentation for all parameters. The description adds no parameter information beyond what's in the schema, so it doesn't enhance understanding of semantics. However, with comprehensive schema coverage, the baseline score of 3 is appropriate as the schema handles the parameter documentation adequately.

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

Purpose3/5

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

The description 'Save a memory to Memory Box' clearly states the action (save) and resource (memory to Memory Box), but it's quite generic. It doesn't specify what a 'memory' is in this context or differentiate this tool from sibling tools like 'update_memory' or 'create_bucket'. The purpose is understandable but lacks specificity.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives. With siblings like 'update_memory', 'create_bucket', and 'search_memories', the description offers no context on prerequisites, appropriate scenarios, or distinctions. The agent must infer usage from the tool name and parameters alone.

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

search_memoriesB

Search for memories using semantic search

ParametersJSON Schema
NameRequiredDescriptionDefault
bucket_idNoFilter to specific bucket
date_sortNoSort semantic search results by date after similarity filtering (default: false)
debugNoInclude debug information in results (default: false)
include_reference_dataNoInclude reference data in response (default: false)
limitNoMaximum number of results to return (1-100, default: 10)
offsetNoNumber of results to skip for pagination (default: 0)
queryYesThe search query (semantic search)
sort_orderNoSort order when date_sort is enabled (default: 'desc')
source_typeNoFilter by source type

TDQS

B3.1/5.0
Behavior2/5

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

With no annotations provided, the description carries full burden but offers minimal behavioral information. It mentions 'semantic search' which implies meaning-based rather than keyword-based matching, but doesn't disclose pagination behavior (implied by offset/limit), rate limits, authentication requirements, or what constitutes a 'memory' resource. The description adds some context about the search method but leaves critical behavioral traits unspecified.

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

Conciseness5/5

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

The description is a single, efficient sentence that states the core functionality without unnecessary words. It's appropriately sized for a search tool and front-loads the essential information. Every word earns its place in conveying the tool's purpose.

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 the complexity (9 parameters, semantic search functionality) and absence of both annotations and output schema, the description is minimally complete. It identifies the core operation but lacks context about what 'memories' are, how results are structured, or performance characteristics. The schema handles parameter documentation well, but the description doesn't compensate for missing behavioral and output context.

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?

Schema description coverage is 100%, so the schema already documents all 9 parameters thoroughly with descriptions, constraints, and defaults. The description adds no parameter-specific information beyond what's in the schema. The baseline score of 3 reflects adequate parameter documentation entirely through the schema, with no additional value from the description.

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

Purpose4/5

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

The description clearly states the verb ('search') and resource ('memories') with the specific method 'semantic search'. It distinguishes from siblings like 'get_all_memories' (which presumably retrieves all without search) and 'get_related_memories' (which likely finds related items rather than semantic search). However, it doesn't explicitly differentiate from potential text-based search tools if they existed.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when semantic search is appropriate compared to other search methods, nor does it reference sibling tools like 'get_all_memories' or 'get_related_memories' for context. The agent must infer usage from the tool name alone.

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

update_memoryC

Update an existing memory including text, bucket, and relationships

ParametersJSON Schema
NameRequiredDescriptionDefault
bucket_idNoMove memory to different bucket
memory_idYesThe ID of the memory to update
raw_contentNoNew raw content for the memory
reference_dataNoUpdated reference data (same structure as save_memory)
source_typeNoUpdate source type
textNoNew text content for the memory

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations provided, the description carries full burden but offers minimal behavioral insight. It states 'Update an existing memory' which implies mutation, but doesn't disclose permissions needed, whether changes are reversible, rate limits, or what happens to unspecified fields. The mention of 'relationships' hints at complexity but lacks operational details.

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

Conciseness5/5

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

Extremely concise single sentence with zero waste. Front-loaded with the core action ('Update an existing memory') followed by specific updatable elements. Every word contributes directly to understanding the tool's function.

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

Completeness2/5

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

For a mutation tool with 6 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain what 'relationships' entail in 'reference_data', doesn't mention the required 'memory_id', and provides no information about return values or error conditions. The schema handles parameter documentation, but behavioral context is severely lacking.

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?

Schema description coverage is 100%, so parameters are well-documented in the schema. The description adds marginal value by listing 'text, bucket, and relationships' which correspond to 'text', 'bucket_id', and 'reference_data' parameters, but doesn't provide additional syntax, format, or constraint details beyond what's in the schema descriptions.

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

Purpose4/5

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

The description clearly states the action ('Update') and resource ('an existing memory'), specifying what can be updated ('including text, bucket, and relationships'). It distinguishes from siblings like 'save_memory' (create) and 'delete_memory' (remove), but doesn't explicitly contrast with all alternatives.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus alternatives like 'save_memory' for creating new memories or 'delete_memory' for removal. It mentions updating 'relationships' but doesn't clarify when that's needed versus other tools. No explicit when-not-to-use or prerequisite information is provided.

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

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 12 tool updatesv1.0.0
    • First observedcheck_memory_status
    • First observedcreate_bucket
    • First observeddelete_bucket
    • First observeddelete_memory
    • First observedget_all_memories
    • First observedget_bucket_memories
    • First observedget_buckets
    • First observedget_related_memories
    • First observedget_usage_stats
    • First observedsave_memory
    • First observedsearch_memories
    • First observedupdate_memory

TDQS

A3.5/5.0

Scored across 12 tools

Disambiguation5/5

Each tool has a clearly distinct purpose with no significant overlap. Tools target specific actions on distinct resources like memories, buckets, or system status, making it easy for an agent to select the right one. For example, get_all_memories vs. get_bucket_memories vs. search_memories are well-differentiated by scope and method.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern using snake_case, such as create_bucket, delete_memory, and get_usage_stats. This uniformity makes the set predictable and easy to parse, with no deviations in style or convention across the 12 tools.

Tool Count5/5

With 12 tools, the server is well-scoped for a memory management system, covering core operations without bloat. Each tool earns its place by addressing key needs like CRUD for memories and buckets, organization, search, and system monitoring, fitting typical expectations for such a domain.

Completeness5/5

The tool surface provides complete CRUD and lifecycle coverage for memories and buckets, including create, read, update, delete, search, and organization features. No obvious gaps exist; agents can perform all essential workflows from saving and retrieving memories to managing buckets and checking status.

Maintenance

ActivityInactive
ResponsivenessNo issues

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