](https://mseep.ai/app/onebirdrocks-ebook-mcp)
电子书MCP
电子书MCP是一个功能强大的模型上下文协议（MCP）服务器，用于处理电子书。建立在 模型上下文协议，它提供了一组标准化的API，用于LLM应用程序和电子书处理功能之间的无缝集成。目前支持EPUB和PDF格式。
用例和价值
电子书MCP通过与您的阅读材料进行自然语言对话，改变了您与数字图书的互动方式。它与Cursor和Claude等现代AI驱动的IDE无缝集成，使您能够：
- 智能图书馆管理：只需问“显示我下载文件夹中的所有EPUB文件”或“在我的库中查找有关GenAI的书籍”
- 互动阅读体验：自然地谈论你的书：
- “给我简要介绍一下《法学硕士工程师手册》” - “第三章涵盖了什么？” - “总结本书中关于RAG的要点”
- 主动学习支持：通过AI驱动的互动增强您的学习：
- “根据第5章中的RAG概念创建一个测验” - “解释本章讨论的架构之间的差异” - “根据本节中的概念给我做实际练习”
- 内容导航：使用自然语言查询轻松浏览您的书籍：
- “查找所有讨论快速工程的章节” - “显示有关微调的章节” - “带我去看关于矢量数据库的部分”
通过弥合传统电子书和人工智能功能之间的差距，Ebook MCP帮助读者通过直观、基于对话的互动从数字图书馆中提取更多价值。
快速演示-使用DeepSeek运行（请使用mcp客户端示例文件夹下的Claude/OpenAI检查所有示例）
Query:Please check all the epub books in my download folder. user id is onebird.
......
Query: Can you ask me a few questions to test my understanding of this book?
Answer: Sure! Here are 5 questions about Elon Musk by Walter Isaacson to test your understanding of the book. Please answer based on your knowledge — I’ll give feedback and add details after each response.
Question 1:
How did Musk’s childhood and family background shape his personality and career later in life?
(Hint: His relationship with his father, growing up in South Africa, etc.)
Question 2:
Zip2 and X.com (later PayPal) were Musk’s early startups. What problems did they solve? How did Musk eventually exit from these companies?
(Hint: Zip2’s business model, X.com’s merger with Confinity, etc.)
Question 3:
In 2008, both SpaceX and Tesla were on the verge of bankruptcy. How did Musk save these two companies?
(Hint: Falcon 1’s fourth launch, NASA contract, Tesla’s last-minute rescue, etc.)
Question 4:
What controversies surround Musk’s management style? What specific incidents in the book illustrate his “hardcore” or “extreme” work culture?
(Hint: Fremont factory’s “production hell,” Twitter layoffs, etc.)
Question 5:
What is Musk’s attitude toward Artificial Intelligence (AI)? Why did he simultaneously support both OpenAI and Neuralink, which seem to have conflicting goals?
(Hint: AI as an existential threat, brain-machine interface vision, etc.)
Please answer each question. I’ll provide feedback and additional details or correct any misunderstandings!
(If a question isn’t clear, feel free to ask me.)
Query:
Question 1: His father’s abusive attitude made him less empathetic towards others.
Question 2: Zip2 solved the problem of electronic maps and online yellow pages. X.com solved online payments.
Question 3: He secured a contract with NASA. Tesla solved its production problems by building a factory in China.
Question 4: I don’t know. Please answer for me.
Question 5: He believes open-source technology is necessary to ensure AI is safe and open.
Answer: Your answers have captured some key points from the book. Let me add details, correct some inaccuracies, and provide further background for Questions 4 and 5:
Question 1 — Correction & Supplement
Influence of His Father:
Musk's father, Errol, was indeed extremely harsh — for example, forcing young Elon to kneel and count grains of rice for hours. The book emphasizes that this emotional desensitization shaped Musk into an extremely goal-oriented person — indifferent to others’ suffering but obsessively committed to his goals.
Reverse Impact:
It’s not that Musk is incapable of empathy — it’s selective. For instance, he may treat employees coldly but personally study medical equipment for his son X’s health issues.
Question 2 — Correction & Supplement
Zip2:
Essentially an online Yellow Pages + map navigation service (helping newspapers go online). Musk wrote much of the early code himself and slept in the office. Eventually, Compaq acquired Zip2 for $307 million (Musk received $22 million).
X.com:
Not just online payments — it was Musk’s attempt to create a comprehensive financial platform (aiming to replace banks). Later merged with Confinity (the precursor of PayPal). Musk was ousted due to internal conflicts, but when eBay acquired PayPal, Musk earned $180 million.
(Note: Musk later bought back the domain X.com — it’s now Twitter’s parent company name).
Question 3 — Correction & Supplement
SpaceX:
In 2008, Falcon 1 succeeded on its fourth launch (after three failures drained their funds). Right after that, SpaceX secured a $1.6 billion NASA contract for cargo resupply — a lifeline for the company.
Tesla:
In 2008, Tesla survived through a $50 million investment from Daimler and a loan from the U.S. Department of Energy.
Building the Gigafactory in China (2019) came much later. In the early years, survival depended on the launch of Model S (2012) and Musk’s personal gamble — selling all his real estate to fund Tesla.
Question 4 — Explanation: Controversy Around His Management Style
“Hardcore” Culture:
At SpaceX/Tesla: Musk demanded employees work 80+ hours per week, even sleeping at the factory. ("If you’re not here, your replacement is.")
After acquiring Twitter: He immediately laid off 75% of staff and asked the remaining employees to sign a "hardcore commitment" — agreeing to long hours and high-intensity output.
Extreme Cases:
At the Fremont Factory: During the "production hell" of the Model 3, Musk slept on the production line and once yelled at employees calling them "worse than dogs" (he later apologized).
Firing Executives: Musk once fired a senior Tesla executive on the spot because the font size in their PowerPoint presentation wasn’t big enough.
Question 5 — Correction & Supplement
AI Threat Theory:
Musk believes that AI could destroy humanity ("more dangerous than nuclear weapons"). Therefore:
OpenAI: He initially supported it to promote safe, open-source AI (but left later due to disputes over control).
Neuralink: He aims to use brain-machine interfaces to merge humans with AI — to prevent humans from being left behind.
Contradictions:
While warning about AI risks, Musk is simultaneously pushing for Full Self-Driving (FSD) technology at Tesla and has founded xAI to research Artificial General Intelligence (AGI).
Overall Evaluation:
✅ You have captured the key events accurately, but the details need to be strengthened (such as timelines and specific figures).
🔍 Recommended areas for further study: Musk's multi-threaded management style (running five companies simultaneously) and his skill in media manipulation (governing through Twitter).特性
EPUB支持
- 提取元数据（标题、作者、出版日期等）
- 摘录目录
- 提取章节内容（带Markdown输出）
- 批量处理EPUB文件
PDF支持
- 提取元数据（标题、作者、创建日期等）
- 摘录目录
- 按页码提取内容
- 按章节标题提取内容
- Markdown输出支持
- 批量处理PDF文件
安装
- 克隆存储库：
git clone https://github.com/yourusername/ebook-mcp.git
cd ebook-mcp- 使用安装依赖项
uv:
uv pip install -e .用法
以开发模式启动MCP服务器
在开发模式下运行服务器：
uv run mcp dev src/ebook_mcp/main.py您可以访问http://localhost:5173/用于测试和调试目的 您还可以为测试安装检查器。
npx @modelcontextprotocol/inspector uv --directory . run src/ebook_mcp/main.py在Prod模式下启动MCP服务器
运行服务器：
uv run src/ebook_mcp/main.py在游标中配置MCP
在Cursor中添加以下配置
"ebook-mcp":{
"command": "uv",
"args": [
"--directory",
"/Users/onebird/github/ebook-mcp/src/ebook_mcp/",
"run",
"main.py"
]
}EPUB处理示例
# Get all EPUB files in a directory
epub_files = get_all_epub_files("/path/to/books")
# Get EPUB metadata
metadata = get_metadata("/path/to/book.epub")
# Get table of contents
toc = get_toc("/path/to/book.epub")
# Get specific chapter content (in Markdown format)
chapter_content = get_chapter_markdown("/path/to/book.epub", "chapter_id")PDF处理示例
# Get all PDF files in a directory
pdf_files = get_all_pdf_files("/path/to/books")
# Get PDF metadata
metadata = get_pdf_metadata("/path/to/book.pdf")
# Get table of contents
toc = get_pdf_toc("/path/to/book.pdf")
# Get specific page content
page_text = get_pdf_page_text("/path/to/book.pdf", 1)
page_markdown = get_pdf_page_markdown("/path/to/book.pdf", 1)
# Get specific chapter content
chapter_content, page_numbers = get_pdf_chapter_content("/path/to/book.pdf", "Chapter 1")api参考
EPUB API
get_all_epub_files(path: str) -> List[str]
获取指定目录中的所有EPUB文件。
get_metadata(epub_path: str) -> Dict[str, Union[str, List[str]]]
从EPUB文件获取元数据。
get_toc(epub_path: str) -> List[Tuple[str, str]]
从EPUB文件中获取目录。
get_chapter_markdown(epub_path: str, chapter_id: str) -> str
获取Markdown格式的章节内容。
PDF API
get_all_pdf_files(path: str) -> List[str]
获取指定目录中的所有PDF文件。
get_pdf_metadata(pdf_path: str) -> Dict[str, Union[str, List[str]]]
从PDF文件获取元数据。
get_pdf_toc(pdf_path: str) -> List[Tuple[str, int]]
从PDF文件中获取目录。
get_pdf_page_text(pdf_path: str, page_number: int) -> str
从特定页面获取纯文本内容。
get_pdf_page_markdown(pdf_path: str, page_number: int) -> str
从特定页面获取Markdown格式的内容。
get_pdf_chapter_content(pdf_path: str, chapter_title: str) -> Tuple[str, List[int]]
按章节标题获取章节内容和相应的页码。
依赖项
关键依赖关系包括：
- ebooklib:EPUB文件处理
- PyPDF2：基本的PDF处理
- PyMuPDF:高级PDF处理
- beautifulsoup4:HTML解析
- html2text：HTML到Markdown的转换
- pydantic：数据验证
- fastmcp:MCP服务器框架
重要提示
- PDF处理依赖于文档的目录。如果TOC不可用，某些功能可能无法工作。
- 对于大型PDF文件，建议按页面范围处理，以避免一次加载整个文件。
- EPUB章节ID必须从目录结构中获得。
建筑
┌────────────────────────────┐
│ Agent Layer │
│ - Translation Strategy │
│ - Style Consistency Check │
│ - LLM Call & Interaction │
└────────────▲─────────────┘
│ Tool Calls
┌────────────┴─────────────┐
│ MCP Tool Layer │
│ - extract_chapter │
│ - write_translated_chapter│
│ - generate_epub │
└────────────▲─────────────┘
│ System/IO Calls
┌────────────┴─────────────┐
│ System Base Layer │
│ - File Reading │
│ - ebooklib Parsing │
│ - File Path Storage/Check│
└────────────────────────────┘贡献
我们欢迎问题和拉取请求！
有关最近更改的详细信息，请参阅 更改日志.md.