MinerU MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| OUTPUT_DIR | No | 转换结果保存路径 | ./downloads |
| USE_LOCAL_API | No | 是否使用本地 API | false |
| MINERU_API_KEY | Yes | MinerU API 密钥（官网申请） | |
| MINERU_API_BASE | No | 远程 API 基础 URL | https://mineru.net |
| LOCAL_MINERU_API_BASE | No | 本地 API 地址（USE_LOCAL_API=true 时生效） | http://localhost:8080 |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| parse_documentsA | 统一接口，将文件转换为Markdown格式。支持本地文件和URL，会根据USE_LOCAL_API配置自动选择合适的处理方式。 |
| get_ocr_languagesB | 获取 OCR 支持的语言列表。 |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 2 tools
The two tools have clearly distinct purposes: get_ocr_languages retrieves a list of supported languages for OCR, while parse_documents converts files to Markdown format. There is no overlap in functionality, making it easy for an agent to select the appropriate tool without confusion.
Both tools follow a consistent verb_noun naming pattern (get_ocr_languages and parse_documents), using snake_case throughout. This predictability enhances readability and usability for agents, with no deviations in style.
With only 2 tools, the server feels thin for a document processing domain that might include OCR and parsing. While the tools cover specific tasks, the scope suggests potential gaps (e.g., no tools for editing, saving, or managing documents), making it borderline too few for comprehensive functionality.
The tools cover basic OCR language retrieval and document parsing, but there are notable gaps in the document processing lifecycle. For example, there are no tools for creating, updating, or deleting documents, which could limit agent workflows and lead to dead ends in more complex tasks.