Omni-Doc-MCP

Omni-Doc-MCP：无需 Java，无需 Python，让 AI 在你的浏览器里直接读懂万物。

Omni-Doc-MCP: no Java, no Python — let AI read everything, right in your browser.

A universal document parsing hub for AI agents. Extract text and structure from PDF, Word (.docx) and Excel (.xlsx / .xls / .csv) and convert them to LLM-friendly Markdown — exposed through a standard MCP (Model Context Protocol) server, a CLI, and a drag-and-drop web demo.

100% pure Node.js + TypeScript. Zero native C++ compilation, zero JVM, zero Python runtime. Runs anywhere Node 18+ runs — including a stock Windows 7 box.

English

Why not Apache Tika?

Tika is the heavyweight champion of document parsing — but it drags a JVM along everywhere it goes. On memory-constrained or legacy hosts (think 8 GB Windows 7 machines), provisioning Java just to read a spreadsheet is a non-starter.

Omni-Doc-MCP takes the pure-JavaScript route:

The parsing engines are battle-tested open-source pure-JS libraries:

• PDF → pdfjs-dist (Mozilla's PDF engine, the same one inside Firefox)

• Word (.docx) → mammoth (docx → clean HTML), compiled to Markdown by our own zero-dependency HTML→Markdown converter

• Excel (.xlsx/.xls/.csv) → SheetJS (xlsx)

("Zero-dependency" here means: no JVM, no Python, no native C++ compilation — nothing that needs a toolchain beyond npm install. The three runtime libraries above are pure JavaScript.)

Project layout

omni-doc-mcp/
├── bin/omni-doc.js              # CLI launcher (boots the compiled TS)
├── src/
│   ├── bin/omni-doc.ts          # CLI: parse / --formats / --serve
│   ├── doc_parsers/             # The pure-JS document engines
│   │   ├── types.ts             # Shared contracts (Parser, ParseResult, errors)
│   │   ├── pdf.parser.ts        # pdfjs-dist, page-by-page text + line rebuild
│   │   ├── word.parser.ts       # mammoth docx → HTML → Markdown
│   │   ├── excel.parser.ts      # SheetJS sheets → Markdown tables / JSON
│   │   ├── html-to-markdown.ts  # Hand-rolled, zero-dep HTML → Markdown
│   │   └── index.ts             # parseDocument() registry + listSupportedFormats()
│   └── mcp_server/server.ts     # Hand-rolled stdio MCP (JSON-RPC 2.0)
├── demo/index.html              # Single-file drag-and-drop web demo
├── tests/
│   ├── generate-fixtures.ts     # Code-generates a real PDF, DOCX, XLSX, CSV
│   ├── parser.test.ts           # Parse-chain suite (Node test runner)
│   └── mcp-probe.ts             # Manual MCP protocol smoke probe
└── package.json

Quick start

git clone https://github.com/<your-user>/omni-doc-mcp.git
cd omni-doc-mcp
npm install          # pure-JS deps only — no native build step
npm run build        # tsc → dist/
npm test             # builds, generates fixtures, runs the suite (11 tests)

CLI

node bin/omni-doc.js ./test.pdf                    # print extracted Markdown
node bin/omni-doc.js ./sheet.xlsx --format json    # structured JSON output
node bin/omni-doc.js ./big.pdf --max-pages 5       # cap PDF pagination
node bin/omni-doc.js --formats                     # list supported formats
node bin/omni-doc.js --serve --port 4321           # launch the web demo

Web demo

npm run demo        # → http://127.0.0.1:4321

Drag a PDF / DOCX / XLSX onto the page (or click to browse). The file is posted to the local server, parsed in-process, and previewed as rendered Markdown — with a raw-Markdown source tab. Nothing leaves your machine.

MCP server (for AI agents)

npm run mcp         # stdio JSON-RPC 2.0 server

Tools exposed:

Mount it on an MCP client, e.g. Claude Desktop (claude_desktop_config.json):

{
  "mcpServers": {
    "omni-doc-mcp": {
      "command": "node",
      "args": ["D:/Code/omni-doc-mcp/dist/src/mcp_server/server.js"]
    }
  }
}

The server implements the MCP stdio transport by hand (newline-delimited JSON-RPC 2.0): initialize with protocol-version negotiation, tools/list, tools/call, graceful notifications/* handling, and standard error codes (-32700, -32600, -32601, -32602, -32603). Parse failures inside a tool come back as isError tool results so the agent can react, instead of crashing the transport.

Programmatic use

import { parseDocument, listSupportedFormats } from 'omni-doc-mcp';

const result = await parseDocument('./report.pdf', { outputFormat: 'markdown', maxPages: 10 });
console.log(result.markdown);   // "## Page 1\n\n..."
console.log(result.meta);       // { format: 'pdf', numPages: 12, parsedPages: 10 }

Notes & limitations

• The @napi-rs/canvas / DOMMatrix warnings you may see on stderr come from pdfjs-dist probing for an optional canvas renderer. Text extraction does not use it; the warnings are harmless.

• Old binary .doc (Word 97-2003) is out of scope for the pure-JS stack — convert to .docx first.

• Scanned PDFs without a text layer yield no text (no OCR on purpose — that would need a native runtime).

Related MCP server: groupdocs-markdown-mcp

中文

为什么不用 Apache Tika？

Tika 是文档解析领域的王者，但它随身拖着一个 JVM。在内存紧张的老机器上（比如 8G 内存的 Win7），为了读一张表格而装一套 Java 环境并不划算。

Omni-Doc-MCP 走纯 JS 路线：解析引擎全部是久经考验的开源纯 JavaScript 库（pdfjs-dist / mammoth / SheetJS），我们自己实现 HTML→Markdown 转换与 MCP 协议层，不引入任何 JNI、WASM 之外的二进制依赖，也不需要 C++ 编译工具链。

快速开始

git clone https://github.com/<your-user>/omni-doc-mcp.git
cd omni-doc-mcp
npm install          # 仅纯 JS 依赖，无原生编译
npm run build        # tsc → dist/
npm test             # 构建 → 生成测试文件 → 跑测试（11 项全绿）

命令行

node bin/omni-doc.js ./test.pdf                    # 输出 Markdown
node bin/omni-doc.js ./sheet.xlsx --format json    # 结构化 JSON
node bin/omni-doc.js ./big.pdf --max-pages 5       # 限制 PDF 页数
node bin/omni-doc.js --formats                     # 支持格式列表
node bin/omni-doc.js --serve --port 4321           # 启动网页演示

网页演示

npm run demo        # → http://127.0.0.1:4321

把 PDF / DOCX / XLSX 文件拖进页面即可预览解析出的 Markdown，也能切到源码视图。文件只在本地解析，不上传任何远端。

MCP 服务器（给 AI Agent 用）

npm run mcp         # stdio JSON-RPC 2.0 服务器

在 Claude Desktop 等 MCP 客户端中挂载（claude_desktop_config.json）：

{
  "mcpServers": {
    "omni-doc-mcp": {
      "command": "node",
      "args": ["D:/Code/omni-doc-mcp/dist/src/mcp_server/server.js"]
    }
  }
}

服务器手写了 MCP stdio 传输层（换行分隔的 JSON-RPC 2.0）：initialize 协议版本协商、tools/list、tools/call、静默处理 notifications/*、标准错误码（-32700/-32600/-32601/-32602/-32603）。工具内部解析失败以 isError 结果返回，让 Agent 自己决定如何应对，而不是搞崩传输层。

编程式调用

import { parseDocument } from 'omni-doc-mcp';

const result = await parseDocument('./report.pdf', { outputFormat: 'json', maxPages: 10 });
console.log(result.json);   // { format, numPages, parsedPages, pages: [...] }

说明与边界

• 终端里可能看到的 @napi-rs/canvas / DOMMatrix 警告来自 pdfjs-dist 对可选画布渲染器的探测，纯文本提取用不到它，可忽略。

• 旧版二进制 .doc（Word 97-2003）不在纯 JS 技术栈范围内，请先转成 .docx。

• 没有文字层的扫描件 PDF 提取不出文本（刻意不做 OCR——那需要原生运行时）。

参与贡献

欢迎 Issue 与 PR：新增解析器请实现 src/doc_parsers/types.ts 中的 DocumentParser 接口，并在 src/doc_parsers/index.ts 注册。

License

MIT — see LICENSE.