mineru-docparse-mcp
Converts Word, PDF, PPT, and Excel documents to Markdown using the MinerU DocParse API. Supports synchronous parsing and async background tasks for large files.
README
mineru-docparse-mcp
把 Word / PDF / PPT / Excel 转成 Markdown 的 MCP Server，基于 MinerU DocParse API。
本项目只是协议封装层，本身不解析文档。使用前需要有一个可访问的 MinerU DocParse 服务，默认地址
http://localhost:8000。部署方式见 MinerU 官方仓库。
安装
pip install mineru-docparse-mcp
配置到 Claude Code
{
"mcpServers": {
"mineru": {
"command": "mineru-docparse-mcp",
"env": {
"MINERU_API_URL": "http://localhost:8000"
}
}
}
}
配好之后就能用了，Claude 会自动调用下面这些工具。
工具
| 工具 | 用途 |
|---|---|
mineru_parse_document |
解析文档，等待完成并直接返回结果（默认用这个） |
mineru_submit_task |
提交大文件到后台解析，立即返回 task_id |
mineru_get_task_status |
查询后台任务进度 |
mineru_get_task_result |
后台任务完成后取结果 |
mineru_health_check |
检查 MinerU 服务是否正常 |
普通文件直接说"帮我解析这个 PDF"就行，Claude 会用 mineru_parse_document。文件很大（上百页）时会自动改用后台任务的三个工具轮询。
常用环境变量
| 变量 | 默认值 | 作用 |
|---|---|---|
MINERU_API_URL |
http://localhost:8000 |
MinerU 服务地址 |
MINERU_OUTPUT_DIR |
无 | 解析结果默认保存目录，设置后不用每次都指定路径 |
MINERU_API_TIMEOUT |
600 |
请求超时秒数，大文件超时可调大 |
设置 MINERU_OUTPUT_DIR 后，配置就变成这样，之后所有结果都存这里，除非你临时指定别的路径：
{
"mcpServers": {
"mineru": {
"command": "mineru-docparse-mcp",
"env": {
"MINERU_API_URL": "http://localhost:8000",
"MINERU_OUTPUT_DIR": "/Users/yourname/Documents/mineru-output"
}
}
}
}
远程部署（可选）
如果想把 MCP 服务架在一台机器上，让多个客户端远程连接，用 HTTP 模式启动：
MCP_TRANSPORT=streamable-http MCP_PORT=8001 mineru-docparse-mcp
客户端这边改成连 URL：
{
"mcpServers": {
"mineru": {
"type": "streamableHttp",
"url": "http://<服务器地址>:8001/mcp"
}
}
}
不写 MCP_TRANSPORT 时默认是本地 stdio 模式（上面"配置到 Claude Code"那种），日常个人使用用默认模式就够了，不需要额外配置。
常见问题
提示"无法连接 MinerU 服务" — 确认 MINERU_API_URL 能访问：curl $MINERU_API_URL/health。stdio 模式下环境变量要写在 MCP 配置的 env 里，写在自己终端的 export 里不生效。
提示"未指定 output_dir" — 要么对话里说清楚存哪，要么按上面配置 MINERU_OUTPUT_DIR。
大文件一直超时 — 换 mineru_submit_task 走后台任务，或调大 MINERU_API_TIMEOUT。
License
MIT
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.