Skip to main content
Glama

무제한 MCP 서버(v0.1.0)

버전특허

Limitless API를 통해 Limitless Pendant 데이터를 Claude, Windsurf 등의 AI 도구에 연결하는 MCP(Model Context Protocol) 서버입니다. AI 채팅 인터페이스와 에이전트가 구조화되고 프로그래밍 가능한 방식으로 Lifelog와 상호 작용할 수 있도록 지원합니다. 한 번에 하나의 컨텍스트가 풍부한 상호 작용을 통해 더욱 체계적이고 지능적인 미래를 만들어 갑시다.

MCP란 무엇인가요?
모델 컨텍스트 프로토콜(Model Context Protocol) 은 AI 모델을 외부 도구 및 데이터에 연결하는 개방형 표준입니다. USB-C 포트나 AI용 HTTP 프로토콜과 같은 개념으로, 범용적이고 안정적이며 확장성을 고려하여 설계되었습니다. 모두가 채택하는 표준입니다. 풍부한 통합, 맞춤형 워크플로, 그리고 AI와 일상적으로 사용하는 도구 간의 원활한 통신을 지원합니다.

중요 참고: 2025년 3월부터 Limitless API는 Limitless Pendant를 통해 기록된 데이터를 필요로 합니다 . 이 서버는 Limitless Pendant에서 기록된 실제 데이터에 의존하며, 이 데이터가 없으면 의미 있는 결과를 반환하지 않습니다. Pendant가 연결되어 있고 기록 중인지 확인하세요.

API 상태 및 향후 계획:

  • 공식 Limitless API는 현재 베타 버전 입니다. 따라서 가끔 불안정하거나, 변경되거나, 일시적인 서비스 중단이 발생할 수 있습니다.

  • 대량의 데이터 요청(예: 수백 개의 로그 나열 또는 검색) 시 API 또는 네트워크 제약으로 인해 시간 초과 오류(예: 504 게이트웨이 시간 초과)가 발생할 수 있습니다. 서버는 이를 완화하기 위해 API 호출당 120초의 시간 초과를 설정하지만, 매우 큰 규모의 요청은 여전히 실패할 수 있습니다.

  • Limitless API는 현재 활발하게 개발 중입니다. 이 MCP 서버는 공식 API에 새로운 기능과 개선 사항이 추가되는 대로 업데이트될 예정입니다.

  • 이 MCP 서버의 버전 0.2.0은 이미 개발 중이며, 가까운 미래에 더욱 강력한 기능과 잠재적으로 새로운 도구를 추가할 계획입니다!

기능(v0.1.0)

  • 라이프로그 목록/가져오기: 펜던트 녹음 파일을 ID, 날짜, 날짜 범위별로 검색하거나 최근 항목을 나열합니다. 정렬 방향( asc / desc )도 제어할 수 있습니다.

  • 최근 로그 검색: 구성 가능한 수의 최근 펜던트 녹음 내용 내에서 간단한 텍스트 검색을 수행합니다(참고: 최근 로그만 검색 가능하며, 전체 기록 검색은 지원되지 않습니다).

이 서버를 사용하면 Lifelog에서 작업 항목을 끌어와 Claude, ChatWise, Windsurf 또는 MCP를 지원하는 다른 AI 어시스턴트/앱을 통해 Notion으로 직접 보내는 등의 작업을 수행할 수 있습니다.

Related MCP server: BeeMCP

필수 조건

  • Node.js(v18 이상 필요)

  • npm 또는 yarn

  • Limitless 계정 및 API 키( 여기서 받으세요 )

  • 무한한 펜던트 (데이터 필요)

  • stdio 서버를 생성하고 환경 변수를 전달할 수 있는 MCP 클라이언트 애플리케이션(예: Claude, Windsurf, Cursor, ChatWise, ChatGPT(곧 출시!))

설정

  1. 이 프로젝트를 복제하거나 다운로드하세요.

  2. 디렉토리로 이동합니다:

    지엑스피1

  3. 종속성 설치:

    npm install
  4. 코드를 작성하세요:

    npm run build

구성(클라이언트 측)

이 서버는 MCP 클라이언트에서 실행될 때 LIMITLESS_API_KEY 환경 변수 로 제공될 것으로 예상합니다.

MCP 클라이언트 설정 파일에 서버 구성 블록을 추가해야 합니다. 아래는 이 블록을 첫 번째 서버로 추가하는지, 아니면 기존 서버와 함께 추가하는지에 따라 달라지는 두 가지 예시입니다.

예시 A: 첫 번째/유일한 서버로 추가

클라이언트의 구성 파일에 현재 빈 mcpServers 개체( "mcpServers": {} )가 있는 경우 이를 다음으로 바꾸세요.

{
  "mcpServers": {
    "limitless": {
      "command": "node",
      "args": ["<FULL_FILE_PATH_TO_DIST_SERVER.js>"],
      "env": {
        "LIMITLESS_API_KEY": "<YOUR_LIMITLESS_API_KEY_HERE>"
      }
    }
  }
}

예시 B: 기존 서버에 추가

mcpServers 객체에 이미 다른 서버가 포함되어 있는 경우(예: "notion": {...} ), "limitless" 블록을 그 옆에 추가하여 올바른 JSON 구문(항목 사이에 쉼표 사용)을 보장합니다.

{
  "mcpServers": {
    "some_other_server": {
      "command": "...",
      "args": ["..."],
      "env": {
        "EXAMPLE_VAR": "value"
      }
    },
    "limitless": {
      "command": "node",
      "args": ["<FULL_FILE_PATH_TO_DIST_SERVER.js>"],
      "env": {
        "LIMITLESS_API_KEY": "<YOUR_LIMITLESS_API_KEY_HERE>"
      }
    }
  }
}

중요한:

  • <FULL_FILE_PATH_TO_DIST_SERVER.js> 빌드된 서버 스크립트의 올바른 절대 경로 (예: /Users/yourname/Documents/MCP/mcp-limitless-server/dist/server.js )로 바꾸세요. 상대 경로는 클라이언트에 따라 안정적으로 작동하지 않을 수 있습니다.

  • <YOUR_LIMITLESS_API_KEY_HERE> 실제 Limitless API 키로 바꾸세요.

  • MCP 구성 파일에는 주석을 포함할 수 없습니다 . <YOUR_LIMITLESS_API_KEY_HERE> 와 같은 자리 표시자 텍스트를 제거하고 실제 키로 바꾸세요.

서버 실행(클라이언트를 통해)

npm start 직접 실행하지 마세요.

  1. 서버가 성공적으로 빌드되었는지 확인합니다( npm run build ).

  2. 위에 표시된 대로 MCP 클라이언트를 구성하세요.

  3. MCP 클라이언트 애플리케이션을 시작하세요. 필요할 때 mcp-limitless-server 프로세스가 자동으로 실행됩니다.

노출된 MCP 도구(v0.1.0)

(자세한 내용은 src/server.ts 참조하거나 클라이언트를 통해 서버에 문의하세요.)

  1. limitless_get_lifelog_by_id : 특정 ID로 단일 펜던트 녹음을 검색합니다.

  2. limitless_list_lifelogs_by_date : 특정 날짜의 펜던트 녹음을 나열합니다.

  3. limitless_list_lifelogs_by_range : 날짜/시간 범위 내의 펜던트 녹음을 나열합니다.

  4. limitless_list_recent_lifelogs : 가장 최근의 Pendant 녹음을 나열합니다.

  5. limitless_search_lifelogs : 최근 Pendant 녹음의 제목/내용을 검색합니다(범위가 제한됨!).

참고사항 및 제한사항

🚫 펜던트 필요
이 서버는 Limitless Pendant에서 생성된 데이터를 사용합니다.

🧪 API 베타 상태
Limitless API는 베타 버전이므로 가끔 불안정하거나 속도 제한이 발생할 수 있습니다. 대량 요청은 시간 초과(예: 504 오류)로 이어질 수 있습니다.

🔍 검색 범위
limitless_search_lifelogs 제한된 수의 최근 로그(기본 20개, 최대 100개)만 검색합니다. 전체 기록을 검색 하지 않으므로 , 더 광범위한 분석을 위해서는 목록 도구를 먼저 사용하세요.

⚠️ 오류 처리 및 시간 초과
API 오류는 MCP 오류 결과로 변환됩니다. 각 API 호출에는 120초의 시간 제한이 있습니다.

🔌 운송
이 서버는 stdio 사용하며 MCP 호환 클라이언트 앱에서 실행되도록 설계되었습니다.

기여하다

아이디어, 개선 사항 또는 피드백이 있으신가요? 이슈를 열거나 PR을 통해 의견을 남겨주세요. 기여는 언제나 환영합니다! 웨어러블 컨텍스트와 지능형 도구를 통해 가능성의 한계를 끊임없이 넓혀 나가도록 함께 노력해 주세요. https://github.com/ipvr9/mcp-limitless-server

Available Tools

5 tools
limitless_get_lifelog_by_idC

Retrieves a single lifelog or Pendant recording by its specific ID.

ParametersJSON Schema
NameRequiredDescriptionDefault
lifelog_idYesThe unique identifier of the lifelog to retrieve.
includeMarkdownNoInclude markdown content in the response.
includeHeadingsNoInclude headings content in the response.

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries full burden. It states 'Retrieves' implying a read-only operation, but doesn't disclose behavioral traits such as authentication requirements, rate limits, error handling, or what happens if the ID is invalid. For a tool with no annotations, 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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded with the core action, 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?

Given no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., the structure of a lifelog, what 'markdown' or 'headings' content entails), leaving the agent uncertain about the response format. For a retrieval tool with rich data, 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 fully documents the three parameters. The description adds no additional meaning beyond implying retrieval by ID, which is already covered in the schema. This meets the baseline of 3 where the schema does the heavy lifting.

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 ('Retrieves') and resource ('a single lifelog or Pendant recording'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'limitless_get_full_transcript' or 'limitless_get_detailed_analysis' that might also retrieve lifelog content but with different scopes or formats.

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 scenarios like needing a specific ID, nor does it reference sibling tools (e.g., 'limitless_list_lifelogs_by_date' for listing multiple lifelogs), leaving the agent without context for selection.

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

limitless_list_lifelogs_by_dateB

Lists logs/recordings for a specific date. Best for getting raw log data which you can then analyze for summaries, action items, topics, etc.

ParametersJSON Schema
NameRequiredDescriptionDefault
dateYesThe date to retrieve lifelogs for, in YYYY-MM-DD format.
limitNoMaximum number of lifelogs to return (Max: 100). Fetches in batches from the API if needed.
timezoneNoIANA timezone for date/time parameters (defaults to server's local timezone).
includeMarkdownNoInclude markdown content in the response.
includeHeadingsNoInclude headings content in the response.
directionNoSort order ('asc' for oldest first, 'desc' for newest first).

TDQS

B3.2/5.0
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 mentions the tool is for 'getting raw log data' and analysis, but doesn't disclose behavioral traits like whether it's read-only, has rate limits, authentication needs, or what the response format looks like. The description adds minimal context beyond the basic purpose.

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 concise and front-loaded with the core purpose in the first sentence. The second sentence adds useful context about usage. Both sentences earn their place, though it could be slightly more structured (e.g., explicitly mentioning sibling tools).

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 no annotations and no output schema, the description is moderately complete for a list tool. It covers the purpose and usage context but lacks details on behavioral traits (e.g., pagination, error handling) and output format, which are important for a tool with 6 parameters and no structured output documentation.

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 parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema, such as explaining how 'date' interacts with 'timezone' or the implications of 'includeMarkdown'. Baseline 3 is appropriate when the schema does the heavy lifting.

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 tool's purpose: 'Lists logs/recordings for a specific date.' It specifies the verb ('Lists') and resource ('logs/recordings'), but doesn't explicitly differentiate from siblings like 'limitless_list_lifelogs_by_range' or 'limitless_list_recent_lifelogs' beyond the date specificity.

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

Usage Guidelines3/5

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

The description provides some usage guidance: 'Best for getting raw log data which you can then analyze for summaries, action items, topics, etc.' This implies when to use it (for raw data analysis), but doesn't explicitly state when not to use it or name alternatives among the sibling tools.

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

limitless_list_lifelogs_by_rangeA

Lists logs/recordings within a date/time range. Best for getting raw log data which you can then analyze for summaries, action items, topics, etc.

ParametersJSON Schema
NameRequiredDescriptionDefault
startYesStart datetime filter (YYYY-MM-DD or YYYY-MM-DD HH:mm:SS).
endYesEnd datetime filter (YYYY-MM-DD or YYYY-MM-DD HH:mm:SS).
limitNoMaximum number of lifelogs to return (Max: 100). Fetches in batches from the API if needed.
timezoneNoIANA timezone for date/time parameters (defaults to server's local timezone).
includeMarkdownNoInclude markdown content in the response.
includeHeadingsNoInclude headings content in the response.
directionNoSort order ('asc' for oldest first, 'desc' for newest first).

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 mentions the tool is for listing raw log data, implying a read-only operation, but does not specify permissions, rate limits, or response format details. The description adds some context about data analysis use but lacks comprehensive behavioral traits like pagination or error handling.

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 front-loaded with the core purpose in the first sentence and adds a concise usage guideline in the second. Both sentences earn their place by providing clear value without redundancy, making it efficient 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 (7 parameters, no output schema, no annotations), the description is moderately complete. It covers purpose and usage but lacks details on behavioral aspects like response format, error cases, or prerequisites. Without annotations or output schema, more context on what the tool returns would be beneficial for full completeness.

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 all 7 parameters thoroughly. The description does not add any parameter-specific semantics beyond what the schema provides, such as explaining interactions between parameters or default behaviors. Baseline 3 is appropriate as the schema handles parameter documentation adequately.

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 verb ('Lists') and resource ('logs/recordings') with specific scope ('within a date/time range'). It distinguishes from siblings by emphasizing raw log data for analysis, unlike tools like 'limitless_get_lifelog_by_id' (single log) or 'limitless_list_lifelogs_by_date' (date-specific).

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 for when to use this tool ('Best for getting raw log data which you can then analyze for summaries, action items, topics, etc.'). However, it does not explicitly state when not to use it or name specific alternatives among the siblings, such as 'limitless_list_recent_lifelogs' for recent logs without date ranges.

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

limitless_list_recent_lifelogsA

Lists the most recent logs/recordings (sorted newest first). Best for getting raw log data which you can then analyze for summaries, action items, topics, etc.

ParametersJSON Schema
NameRequiredDescriptionDefault
limitNoNumber of recent lifelogs to retrieve (Max: 100). Defaults to 10.
timezoneNoIANA timezone for date/time parameters (defaults to server's local timezone).
includeMarkdownNoInclude markdown content in the response.
includeHeadingsNoInclude headings content in the response.

TDQS

A3.7/5.0
Behavior3/5

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 mentions sorting ('newest first') and the nature of the data ('raw log data'), which adds useful context. However, it lacks details on permissions, rate limits, pagination, or what the response format looks like (e.g., structure of returned logs). This leaves gaps for a tool with no 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 concise and well-structured with two sentences: the first states the core functionality, and the second provides usage guidance. Every sentence adds value without redundancy, making it easy to parse and front-loaded with key information.

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 no annotations and no output schema, the description is moderately complete. It covers purpose and usage but lacks behavioral details (e.g., response format, error handling) and doesn't fully compensate for the absence of structured output information. For a list tool with 4 parameters, it's adequate but has clear gaps in transparency.

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 fully documents all 4 parameters (limit, timezone, includeMarkdown, includeHeadings). The description doesn't add any parameter-specific information beyond what's in the schema, such as explaining how 'limit' interacts with 'recent' or the implications of the boolean flags. Baseline 3 is appropriate when schema does the heavy lifting.

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 tool's purpose: 'Lists the most recent logs/recordings (sorted newest first).' It specifies the verb ('lists'), resource ('logs/recordings'), and sorting behavior. However, it doesn't explicitly differentiate from siblings like 'limitless_list_lifelogs_by_date' or 'limitless_list_lifelogs_by_range' beyond mentioning 'recent' and 'newest first.'

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 usage context: 'Best for getting raw log data which you can then analyze for summaries, action items, topics, etc.' This implies when to use it (for raw data analysis) but doesn't explicitly state when not to use it or name alternatives among the sibling tools, such as when date-based filtering is needed.

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

limitless_search_lifelogsA

Performs a simple text search for specific keywords/phrases within the title and content of recent logs/Pendant recordings. Use ONLY for keywords, NOT for concepts like 'action items' or 'summaries'. Searches only recent logs (limited scope).

ParametersJSON Schema
NameRequiredDescriptionDefault
search_termYesThe text to search for within lifelog titles and content.
fetch_limitNoHow many *recent* lifelogs to fetch from the API to search within (Default: 20, Max: 100). This defines the scope of the search, NOT the number of results returned.
limitNoMaximum number of lifelogs to return (Max: 100). Fetches in batches from the API if needed.
timezoneNoIANA timezone for date/time parameters (defaults to server's local timezone).
includeMarkdownNoInclude markdown content in the response.
includeHeadingsNoInclude headings content in the response.

TDQS

A4.1/5.0
Behavior3/5

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

With no annotations provided, the description carries full burden. It discloses important behavioral traits: the search is limited to recent logs, it searches both title and content, and it's keyword-based (not conceptual). However, it doesn't mention authentication requirements, rate limits, error conditions, or what the response format looks like. For a search tool with 6 parameters, this leaves significant behavioral aspects undocumented.

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?

Three concise sentences with zero waste. Each sentence adds distinct value: first states the core function, second provides critical usage restrictions, third clarifies scope limitation. The description is appropriately sized and front-loaded with essential information.

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?

For a search tool with 6 parameters and no output schema, the description provides good purpose and usage guidance but lacks behavioral details about authentication, rate limits, error handling, and response format. The absence of annotations means the description should compensate more for behavioral transparency, which it only partially addresses. It's adequate but has clear gaps for a tool of this complexity.

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 parameters thoroughly. The description adds some context about 'recent' logs which relates to fetch_limit's scope, but doesn't provide additional parameter semantics beyond what's in the schema. This meets the baseline expectation when schema coverage is complete.

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 tool's purpose with specific verbs ('performs a simple text search') and resources ('within the title and content of *recent* logs/Pendant recordings'). It distinguishes from siblings by specifying it's for keyword searches only, unlike list/retrieve siblings like limitless_list_lifelogs_by_date or limitless_get_lifelog_by_id.

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?

Explicitly states when to use ('Use ONLY for keywords, NOT for concepts like 'action items' or 'summaries'') and provides context about scope ('Searches only recent logs (limited scope)'). This gives clear guidance on appropriate vs. inappropriate use cases, though it doesn't name specific alternative tools.

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. 5 tool updatesv1.0.0
    • First observedlimitless_get_lifelog_by_id
    • First observedlimitless_list_lifelogs_by_date
    • First observedlimitless_list_lifelogs_by_range
    • First observedlimitless_list_recent_lifelogs
    • First observedlimitless_search_lifelogs

TDQS

A3.6/5.0

Scored across 5 tools

Disambiguation4/5

The tools are mostly distinct in purpose, focusing on different retrieval methods for lifelogs. However, there is some overlap between 'list_lifelogs_by_date', 'list_lifelogs_by_range', and 'list_recent_lifelogs', as all three list logs based on time criteria, which could cause mild confusion about which to use for specific time-based queries.

Naming Consistency5/5

All tool names follow a consistent pattern: they start with 'limitless_' followed by a verb_noun structure (e.g., 'get_lifelog_by_id', 'list_lifelogs_by_date'). This uniformity makes the tool set predictable and easy to navigate.

Tool Count5/5

With 5 tools, the server is well-scoped for its purpose of retrieving lifelogs. Each tool serves a specific function (e.g., by ID, date, range, recency, search), and none seem redundant or missing for basic retrieval operations.

Completeness3/5

The tool set covers retrieval operations comprehensively, but there are notable gaps in the lifecycle. It lacks create, update, or delete tools for lifelogs, which limits agents to read-only interactions. This could cause failures if agents need to modify data.

Maintenance

ActivityInactive
ResponsivenessNo issues

Related MCP Connectors

Related MCP Servers

  • F
    license
    Not graded
    quality
    D
    maintenance
    MCP server that connects Whoop fitness data to Claude, enabling natural language queries about recovery, sleep, workouts, and more.
    -
  • A
    license
    Not graded
    quality
    D
    maintenance
    Unofficial MCP server that bridges AI assistants with Bee wearable lifelogging data, enabling retrieval and management of conversations, facts, todos, and locations.
    51
    MIT