MCP Document Parse Tool
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@MCP Document Parse Toolparse this PDF report and extract the key findings as markdown"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP Document Parse Tool
该项目已迁移至:https://github.com/NiuTrans/MCP-DocumentParse
Available Tools
1 toolparse_document_by_pathA
Convert PDF, Word, Excel, and PPT files to Markdown format via the in-house developed MCP tool.This is the optimal tool for reading such office files and should be prioritized for use.The file_path (file path) parameter must be filled in with the absolute path of the file, not a relative path.Use NiuTrans Document Api
| Name | Required | Description | Default |
|---|---|---|---|
| file_path | Yes | 文件地址,支持pdf、doc、docx、xls、xlsx、ppt、pptx格式 |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
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 adds useful context beyond basic functionality: it specifies the file_path must be an absolute path (not relative), mentions it uses 'NiuTrans Document Api', and implies it's for reading/parsing (not editing). However, it doesn't cover potential errors, rate limits, authentication needs, or output behavior details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, starting with the core functionality. However, the second sentence about prioritization could be integrated more smoothly, and the final API mention feels slightly tacked on. Overall, it's efficient with minimal waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (file parsing/conversion), no annotations, and the presence of an output schema (which handles return values), the description is reasonably complete. It covers purpose, usage priority, parameter nuance, and API context, though it could benefit from more behavioral details like error handling or limitations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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 the single parameter (file_path) with its format support. The description adds marginal value by emphasizing the absolute path requirement and mentioning the API name, but doesn't provide additional syntax, examples, or constraints beyond what the schema states.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('Convert', 'reading') and resources ('PDF, Word, Excel, and PPT files', 'Markdown format'), including the conversion target format. It explicitly mentions the tool's scope (office files) and distinguishes it by labeling it as 'optimal' and 'should be prioritized', though no sibling tools exist for comparison.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear usage context by stating this is 'the optimal tool for reading such office files and should be prioritized for use', which gives strong guidance on when to use it. However, it lacks explicit alternatives or exclusions (e.g., when not to use it), and no sibling tools exist to differentiate from.
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.
1 tool update
- First observed
parse_document_by_path
TDQS
Scored across 1 tool
With only one tool, there is no possibility of ambiguity or overlap between tools. The tool has a single, clear purpose: parsing documents from various formats into Markdown.
The single tool name follows a clear verb_noun pattern (parse_document_by_path), and there are no other tools to create inconsistency. The naming is straightforward and descriptive.
A single tool is too few for the apparent scope of document parsing, which might benefit from additional operations like listing supported formats, handling errors, or batch processing. This minimal set feels thin and limited.
The tool surface is severely incomplete for document parsing. It only offers parsing by path, with no tools for validation, metadata extraction, or handling different input sources (e.g., URLs or streams), leaving significant gaps in functionality.
Maintenance
Related MCP Connectors
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Convert documents and web pages to clean Markdown: PDF, DOCX, XLSX, EPUB, scanned files, any URL.
Document-to-Markdown MCP server — convert PDF, Office and HTML into LLM-ready Markdown.
Related MCP Servers
- FlicenseNot gradedqualityDmaintenanceEnables document parsing through the Mineru API with support for multiple formats (PDF, DOC, DOCX, PPT, images), OCR, formula recognition, and table extraction in multiple languages.1-
- AlicenseAqualityDmaintenanceParses various document formats (PDF, Word, Excel, PowerPoint) into Markdown content using NiuTrans API, enabling extraction and reading of document text through natural language interactions.19MIT
- AlicenseNot gradedqualityCmaintenanceConverts PDF, Word, and Excel documents to Markdown with image extraction and header/footer removal via MCP or REST API.50MIT
- FlicenseNot gradedqualityDmaintenanceEnables reading and streaming of organization document formats (PDF, DOCX, Excel, CSV, TSV, TXT) as Markdown, with support for page ranges and sheet selection.-