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WeRead MCP Server

by freestylefly
OverviewSchemaRelated ServersScoreDiscussions
JavaScript
Hybrid

微信读书 MCP Server 是一个为微信读书提供 MCP（Model Context Protocol）服务的工具，支持将微信读书的书籍、笔记和划线数据提供给支持MCP的大语言模型客户端，如Cursor、Claude Desktop。

功能特点

  • 从微信读书获取书架信息

  • 搜索书架中的图书

  • 获取图书的笔记和划线

  • 获取图书的热门书评

  • 支持按章节组织笔记和划线

  • 与支持MCP协议的LLM客户端无缝集成

Related MCP server: Notion MCP Server

主要工具

  1. get_bookshelf - 获取用户书架上所有书籍

    • 返回书籍基本信息，包括书名、作者、译者和分类等

  2. search_books - 通过关键词检索用户书架上的书籍

    • 支持模糊匹配和精确匹配

    • 可选是否包含详细信息

    • 可设置最大结果数量

  3. get_book_notes_and_highlights - 获取指定书籍的所有划线和笔记

    • 支持按章节组织结果

    • 支持筛选划线样式

    • 返回结构化的数据以便于LLM理解

  4. get_book_best_reviews - 获取指定书籍的热门书评

    • 支持设置返回数量

    • 支持分页浏览

    • 包含评分、点赞数和评论者信息

安装与使用

先决条件

  • Node.js 16.x 或更高版本

  • 微信读书账号和有效的Cookie

安装教程

详见：

与Claude Desktop集成

有多种方式可以与Claude Desktop集成：

方式一：通过 npx 使用（最简单，推荐）

  1. 打开Claude Desktop

  2. 进入设置 -> MCP配置

  3. 添加工具，使用以下JSON配置：

    {
  "mcpServers": {
    "mcp-server-weread": {
      "command": "npx",
      "args": ["-y", "mcp-server-weread"],
      "env": {
        // 方式1：使用Cookie Cloud（推荐）
        "CC_URL": "https://cc.chenge.ink",  // Cookie Cloud的URL
        "CC_ID": "您的ID",                   // Cookie Cloud的ID
        "CC_PASSWORD": "您的密码"            // Cookie Cloud的密码
        
        // 或方式2：直接提供Cookie
        // "WEREAD_COOKIE": "您的微信读书Cookie"
      }
    }
  }
}

方式二：全局安装后使用

  1. 全局安装包：

    npm install -g mcp-server-weread

  2. 在Claude配置中使用：

    {
  "mcpServers": {
    "mcp-server-weread": {
      "command": "mcp-server-weread",
      "env": {
        // 同上方式配置环境变量
      }
    }
  }
}

提示：直接在Claude配置中提供环境变量的方式更加方便，无需设置.env文件，推荐使用。

CookieCloud 配置说明

为了解决 Cookie 频繁过期，需要重新获取并更新环境变量的问题。本项目支持 CookieCloud 服务来自动同步和更新 Cookie。CookieCloud 是一个开源的跨浏览器 Cookie 同步工具，支持自建服务器。

配置步骤：

安装浏览器插件 Edge商店：CookieCloud for Edge Chrome商店：CookieCloud for Chrome

配置 CookieCloud 插件

服务器地址：使用默认服务器 https://cc.chenge.ink 或填入自建服务器地址 点击 "自动生成密码" 同步域名关键词中填入 "weread" 点击"保存" ，然后点击 "手动同步"确保配置生效 [可选] 如果需要插件自动保活，可以在保活中填入 https://weread.qq.com，插件会自动刷新 Cookie

在MCP Json中配置CookieCloud变量： CC_URL=你的CookieCloud服务器地址 （或使用我的默认服务器地址 https://cc.chenge.ink ） CC_ID=你的CookieCloud用户UUID CC_PASSWORD=你的CookieCloud密码 注意：配置 CookieCloud 后，系统会优先使用 CookieCloud 获取 Cookie，获取失败才会使用 WEREAD_COOKIE 环境变量的值。

Cookie获取方法

微信读书的Cookie可以通过以下步骤获取：

  1. 使用Chrome浏览器登录微信读书网页版

  2. 按F12打开开发者工具，切换到Network标签页

  3. 刷新页面，在请求列表中找到weread.qq.com的请求

  4. 在Headers中找到Cookie字段，复制其完整内容

  5. 将复制的内容添加到MCP Json 或 .env文件的WEREAD_COOKIE变量中

使用示例

以下是一些与LLM对话的示例：

获取书架信息

用户: 帮我查看我的微信读书书架
LLM: 我将获取您的微信读书书架信息。
[LLM调用get_bookshelf工具]
我从您的微信读书书架获取到了208本书籍。以下是部分书籍：
1. 《隐藏的自我》- 大卫·伊格曼
2. 《思考，快与慢》- 丹尼尔·卡尼曼
3. 《人类简史》- 尤瓦尔·赫拉利
...

搜索特定书籍

用户: 帮我找关于心理学的书
LLM: 我将搜索您书架上与心理学相关的书籍。
[LLM调用search_books工具，参数为keyword="心理学"]
在您的书架上，我找到了3本与心理学相关的书籍：
1. 《思考，快与慢》- 丹尼尔·卡尼曼（进度：75%）
2. 《乌合之众》- 古斯塔夫·勒庞（进度：50%）
3. 《心理学与生活》- 理查德·格里格（进度：30%）
您想了解哪一本书的更多信息？

获取笔记和划线

用户: 帮我整理《思考，快与慢》这本书的笔记
LLM: 我将获取《思考，快与慢》的笔记和划线。
[LLM调用search_books工具，找到书籍ID]
[LLM调用get_book_notes_and_highlights工具]
以下是您在《思考，快与慢》中的笔记和划线（按章节组织）：

第一章：系统1和系统2
- 划线：「系统1的运行是无意识且快速的，不怎么费脑力，没有感觉，完全处于自主控制状态。」
- 您的笔记：「系统1负责直觉和快速判断，系统2负责缓慢的理性思考。」

第三章：锚定效应
- 划线：「锚定效应指的是在不确定情境下进行数字估计时，会过度受到事先接触的不相干数字的影响。」
...

获取热门书评

用户: 这本《原则》有哪些热门书评？
LLM: 我会为您查找《原则》的热门书评。
[LLM调用search_books工具，找到书籍ID]
[LLM调用get_book_best_reviews工具]
以下是《原则》的热门书评：

1. 评论者"思考者"（评分：5星）：
   "这是一本关于如何思考的书。达利欧将自己多年的经验总结为可操作的原则，帮助我们做出更好的决策。特别喜欢他关于'痛苦+反思=进步'的观点，非常实用。"
   👍 182 | 💬 23

2. 评论者"投资学习者"（评分：4星）：
   "桥水基金创始人的思想精华，值得反复阅读。书中的工作原则部分对管理者特别有帮助，建议先读生活原则，再读工作原则。"
   👍 94 | 💬 12
...

九、友情链接

  • mcp-server-weread ：🚀一个为微信读书提供MCP（Model Context Protocol）服务的工具，支持将微信读书的书籍、笔记和划线数据提供给支持MCP的大语言模型客户端，如Claude Desktop。

  • CodeCanvas ：📚本代码仓库是作者苍何多年从事一线互联网Java开发的学习历程技术汇总，旨在为大家提供一个清晰详细的学习教程，侧重点更倾向编写Java核心内容。💪🏻

  • PmHub ：🔥PmHub 是一套基于 SpringCloud & LLM 的微服务智能项目管理系统，这个项目旨在帮助小伙伴们快速掌握微服务/分布式项目的架构设计和开发流程，如果想在校招或者社招中拿到一个满意的 offer，PmHub 将是一个非常 nice 的选择。

十、鸣谢

此项目 fork 自 ChenyqThu 的mcp-server-weread项目，做了一些小修改，突然就🔥了，这里也请大家去作者GitHub原项目上star，另外ChenyqThu新的更新我也会做同步，项目也会保持使用教程的更新，感谢大家的喜欢。

十一、star 趋势图

Star History Chart

十二、公众号

微信搜 苍何 或扫描下方二维码关注苍何的原创公众号，回复 AI 即可和 5000+ 好友一同探讨AI，一同学习MCP。

苍何微信公众号

十三、许可证

MIT License (MIT) The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

Copyright (c) 2025-2026 mcp-server-weread

Available Tools

4 tools
get_book_best_reviewsC

Get popular reviews for a specific book

ParametersJSON Schema
NameRequiredDescriptionDefault
book_idYesBook ID
countNoNumber of reviews to return
max_idxNoPagination index
synckeyNoSync key for pagination

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 the full burden of behavioral disclosure. It mentions 'popular reviews' but doesn't explain how popularity is determined (e.g., sorting criteria, algorithm). It also omits key behavioral traits like whether this is a read-only operation, potential rate limits, authentication needs, or what the output format looks like (since no output schema exists). The description adds minimal value 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.

Conciseness5/5

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

The description is a single, efficient sentence with zero waste. It's front-loaded with the core purpose ('Get popular reviews for a specific book'), and every word earns its place. There's no redundant or verbose language.

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 complexity (a tool with 4 parameters, no annotations, and no output schema), the description is incomplete. It doesn't explain behavioral aspects like how 'popular' is defined, pagination mechanics, or return format. With no output schema, the description should ideally hint at what's returned (e.g., list of reviews with ratings), but it doesn't. This leaves significant gaps for an AI agent to use the tool 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%, so the schema already documents all parameters (book_id, count, max_idx, synckey) with descriptions. The description adds no additional meaning about parameters beyond implying 'book_id' is needed for a specific book. It doesn't clarify parameter interactions (e.g., how max_idx and synckey work together for pagination) or semantics of 'popular' in relation to parameters. 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 verb ('Get') and resource ('popular reviews for a specific book'), making the purpose understandable. It distinguishes from siblings like 'get_book_notes_and_highlights' (which focuses on notes/highlights) and 'search_books' (which searches books rather than reviews). However, it doesn't specify what makes reviews 'popular' (e.g., by rating, helpfulness, recency), 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. It doesn't mention when to choose this over 'get_book_notes_and_highlights' for review-related data, or whether it's preferable for popular reviews versus other review-fetching tools not listed. There's no context about prerequisites, timing, or exclusions.

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

get_book_notes_and_highlightsC

Get all highlights and notes for a specific book, organized by chapter

ParametersJSON Schema
NameRequiredDescriptionDefault
book_idYesBook ID
highlight_styleNoHighlight style filter, null means all
include_chaptersNoWhether to include chapter information
organize_by_chapterNoWhether to organize by chapter

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 the full burden. It mentions organization by chapter, which adds some behavioral context, but fails to disclose critical traits such as whether this is a read-only operation, potential rate limits, authentication needs, error conditions, or what the output format looks like (especially since there's no output schema). For a tool with 4 parameters and no annotations, this is a significant gap.

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 purpose ('Get all highlights and notes for a specific book') and adds a useful qualifier ('organized by chapter'). There is no wasted verbiage, and every word earns its place.

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 (4 parameters, no annotations, no output schema), the description is incomplete. It adequately states the purpose but lacks usage guidelines, behavioral transparency (e.g., safety, output format), and doesn't compensate for the absence of an output schema. For a data retrieval tool with multiple parameters, more context is needed to guide 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?

Schema description coverage is 100%, so the schema fully documents all parameters. The description adds minimal value beyond the schema by implying organization by chapter (related to 'organize_by_chapter' parameter) but doesn't provide additional syntax, format details, or clarify interactions between parameters (e.g., how 'include_chapters' and 'organize_by_chapter' relate). 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 verb 'Get' and resource 'highlights and notes for a specific book', with additional context about organization 'by chapter'. It distinguishes from siblings like 'get_book_best_reviews' (reviews vs. notes/highlights) and 'search_books' (searching vs. retrieving specific content). However, it doesn't explicitly differentiate from 'get_bookshelf', which might also involve book-related data retrieval.

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_book_best_reviews' or 'get_bookshelf'. It implies usage for retrieving notes/highlights for a specific book but doesn't specify prerequisites, exclusions, or comparative contexts with sibling tools.

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

get_bookshelfB

Get all books in the user's bookshelf with comprehensive statistics and categorization 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It hints at a read operation ('Get') and output details, but doesn't address critical aspects like authentication requirements, rate limits, error conditions, or whether it's safe for repeated use. This leaves significant gaps for a tool that likely accesses user data.

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 a single, efficient sentence that front-loads the core action ('Get all books') and adds valuable output details. There's no wasted wording, though it could be slightly more structured by explicitly separating purpose from output characteristics.

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 (accessing user data with statistics/categorization), no annotations, and no output schema, the description is minimally adequate. It covers what the tool does but lacks details on behavior, output format, and error handling, which are important for an AI agent to use it correctly.

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 with 100% schema description coverage, so the schema fully documents the absence of inputs. The description appropriately doesn't add parameter details, maintaining focus on the tool's purpose. A baseline of 4 is applied since no parameters exist, and the description doesn't introduce confusion.

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 all books') and resource ('user's bookshelf'), with additional detail about the output including 'comprehensive statistics and categorization information'. However, it doesn't explicitly differentiate from sibling tools like 'search_books' or 'get_book_best_reviews', 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 like 'search_books' or 'get_book_best_reviews'. It mentions the scope ('user's bookshelf') but doesn't specify use cases, prerequisites, or exclusions, leaving the agent without clear selection criteria.

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

search_booksC

Search for books in the user's bookshelf by keywords and return matching books with details and reading progress

ParametersJSON Schema
NameRequiredDescriptionDefault
exact_matchNoWhether to use exact matching, default is fuzzy matching
include_detailsNoWhether to include detailed information
keywordYesSearch keyword to match book title, author, translator or category
max_resultsNoMaximum number of results to return

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 mentions returning 'details and reading progress,' which adds some behavioral context beyond basic search functionality. However, it lacks critical information such as whether this is a read-only operation, potential rate limits, authentication requirements, error conditions, or pagination behavior. The description is insufficient 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.

Conciseness4/5

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

The description is a single, efficient sentence that front-loads the core purpose. It avoids unnecessary words and directly states the action and outcome. However, it could be slightly more structured by separating search criteria from return values for clarity.

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 return values in detail (e.g., what 'details' include, format of 'reading progress'), error handling, or operational constraints. For a search tool with 4 parameters and no structured output, more context is needed to guide 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?

Schema description coverage is 100%, so the schema already documents all parameters (keyword, exact_match, include_details, max_results). The description adds marginal value by implying keyword matching across multiple fields (title, author, translator, category), but this is partially covered in the schema. No additional syntax or format details are provided beyond the schema, meeting the baseline for high 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 tool's purpose: 'Search for books in the user's bookshelf by keywords and return matching books with details and reading progress.' It specifies the verb (search), resource (books in user's bookshelf), and scope (by keywords). However, it doesn't explicitly differentiate from sibling tools like 'get_bookshelf' (which might list all books without searching).

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 sibling tools like 'get_bookshelf' (for listing all books) or 'get_book_best_reviews' (for reviews), nor does it specify prerequisites or exclusions (e.g., when keyword is optional or required). Usage is implied but not explicitly stated.

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. Dates show when Glama detected each change.

  1. 4 tool updatesv1.0.0
    • First observedget_book_best_reviews
    • First observedget_book_notes_and_highlights
    • First observedget_bookshelf
    • First observedsearch_books
Install Server
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TDQS

B3.4/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: get_book_best_reviews retrieves reviews, get_book_notes_and_highlights fetches user annotations, get_bookshelf lists all books with stats, and search_books finds books by keyword. There is no overlap in functionality, making tool selection straightforward for an agent.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern with snake_case: get_book_best_reviews, get_book_notes_and_highlights, get_bookshelf, and search_books. The naming is predictable and readable, with no deviations in style or convention.

Tool Count4/5

With 4 tools, the count is reasonable for a WeRead server focused on book management and reading insights. It covers core operations without being overwhelming, though it might benefit from additional tools for actions like updating notes or managing bookshelves to be fully comprehensive.

Completeness4/5

The tool set provides good coverage for reading and book management, including retrieval of reviews, notes, bookshelf data, and search. Minor gaps exist, such as the inability to create or update notes/highlights or manage bookshelf entries, but agents can still perform key workflows with the available tools.

Maintenance

ActivityInactive
ResponsivenessSyncing

Resources

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