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无限 MCP 服务器 (v0.1.0)

版本执照

这是一个 MCP(模型上下文协议)服务器,它通过Limitless API将您的 Limitless 吊坠数据连接到 Claude、Windsurf 等 AI 工具。它允许 AI 聊天界面和代理以结构化、可编程的方式与您的 Lifelog 进行交互。让我们一起构建一个更有条理、更智能的未来——一次一个丰富的情境互动。

什么是 MCP?
模型上下文协议 (MCP)是一个用于连接 AI 模型和外部工具和数据的开放标准——可以将其视为 AI 的 USB-C 端口,甚至是 HTTP 协议——它通用、可靠,并且专为可扩展性而设计。它是一个人人都采用的标准。它支持丰富的集成、自定义工作流,以及 AI 与您日常使用的工具之间的无缝通信。

重要提示:自 2025 年 3 月起,Limitless API需要通过 Limitless 吊坠记录数据。此服务器依赖于您的 Limitless 吊坠记录的真实数据——如果没有这些数据,它将无法返回任何有意义的信息。请确保您的吊坠已连接并正在记录。

API 状态和未来计划:

  • 官方 Limitless API 目前处于测试阶段。因此,它可能偶尔不可靠、可能发生变更或出现暂时中断。

  • 由于 API 或网络限制,请求大量数据(例如,列出或搜索数百条日志)有时可能会导致超时错误(例如 504 网关超时) 。服务器为每个 API 调用设置了 120 秒的超时时间,以缓解此问题,但非常大的请求仍然可能失败。

  • Limitless API 正在积极开发中。一旦官方 API 中推出新功能和改进,此 MCP 服务器将进行更新。

  • 该 MCP 服务器的0.2.0 版本已在开发中,计划在不久的将来添加更多强大的功能和潜在的新工具!

功能(v0.1.0)

  • **列出/获取生活日志:**按 ID、日期、日期范围检索 Pendant 记录,或列出最近的记录。支持排序方向控制( asc / desc )。

  • **搜索最近的日志:**在可配置数量的最近 Pendant 记录内容中执行简单的文本搜索(注意:只能搜索最近的日志;不支持完整历史记录搜索)。

使用此服务器,您可以从 Lifelog 中提取行动项目并将其直接发送到 Notion——通过 Claude、ChatWise、Windsurf 或任何其他支持 MCP 的 AI 助手/应用程序。

Related MCP server: BeeMCP

先决条件

  • Node.js(需要 v18 或更高版本)

  • npm 或 yarn

  • 无限账户和 API 密钥(在此获取)

  • 无限吊坠(数据所需)

  • MCP 客户端应用程序(例如,Claude、Windsurf、Cursor、ChatWise、ChatGPT(即将推出!))能够生成 stdio 服务器并传递环境变量。

设置

  1. 克隆或下载此项目。

  2. 导航到目录:

    cd mcp-limitless-server
  3. 安装依赖项:

    npm install
  4. 构建代码:

    npm run build

配置(客户端)

此服务器期望当您的 MCP 客户端启动它时,将LIMITLESS_API_KEY作为环境变量提供。

您需要在 MCP 客户端的设置文件中添加一个服务器配置块。以下是两个示例,具体取决于您是将其添加为第一个服务器,还是将其与现有服务器一起添加。

示例 A:添加为第一个/唯一服务器

如果您的客户端的配置文件当前有一个空的mcpServers对象( "mcpServers": {} ),请将其替换为:

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

示例 B:添加到现有服务器

如果您的mcpServers对象已经包含其他服务器(如"notion": {...} ),请在它们旁边添加"limitless"块,确保正确的 JSON 语法(条目之间的逗号):

{
  "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>"
      }
    }
  }
}

重要的:

  • 将<FULL_FILE_PATH_TO_DIST_SERVER.js>替换为构建的服务器脚本的正确绝对路径(例如, /Users/yourname/Documents/MCP/mcp-limitless-server/dist/server.js )。相对路径可能无法可靠地工作,具体取决于客户端。

  • 用您的实际 Limitless API 密钥替换<YOUR_LIMITLESS_API_KEY_HERE> 。

  • MCP 配置文件不能包含注释。请删除所有占位符文本(例如<YOUR_LIMITLESS_API_KEY_HERE> ),并将其替换为您的实际密钥。

运行服务器(通过客户端)

不要直接运行npm start 。

  1. 确保服务器已成功构建( npm run build )。

  2. 按照上面所示配置您的 MCP 客户端。

  3. 启动您的 MCP 客户端应用程序。它会在需要时自动启动mcp-limitless-server进程。

公开的 MCP 工具 (v0.1.0)

(请参阅src/server.ts或通过客户端向服务器询问完整详细信息。)

  1. limitless_get_lifelog_by_id :通过特定 ID 检索单个吊坠记录。

  2. limitless_list_lifelogs_by_date :列出特定日期的吊坠记录。

  3. limitless_list_lifelogs_by_range :列出日期/时间范围内的吊坠记录。

  4. limitless_list_recent_lifelogs :列出最近的吊坠记录。

  5. limitless_search_lifelogs :搜索最近的Pendant 录音的标题/内容(范围有限!)。

注意事项和限制

🚫需要吊坠
该服务器依赖于无限吊坠生成的数据。

🧪 API Beta 状态
Limitless API 尚处于测试阶段,可能会偶尔出现不稳定或速率受限的情况。大量请求可能会导致超时(例如 504 错误)。

🔍搜索范围
limitless_search_lifelogs仅扫描有限数量的近期日志(默认 20 条,最多 100 条)。它不会搜索您的全部历史记录——请优先使用列表工具进行更广泛的分析。

⚠️错误处理和超时
API 错误会被转换为 MCP 错误结果。每次 API 调用的超时时间为 120 秒。

🔌交通
该服务器使用stdio并由 MCP 兼容的客户端应用程序启动。

贡献

有任何想法、改进或反馈?欢迎随时提交问题或 PR——我们随时欢迎大家贡献代码!让我们继续探索可穿戴环境和智能工具的无限可能。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

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