MCP Document Parse Tool
Click on "Install 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 mentions the tool uses 'NiuTrans Document Api' and requires absolute paths, which adds useful context. However, it doesn't disclose important behavioral traits like error handling, rate limits, authentication needs, or what happens with unsupported files, leaving significant gaps.
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 with four sentences that each add value: purpose statement, usage priority, parameter guidance, and API mention. It's front-loaded with the core functionality. However, the last sentence about the API feels slightly disconnected, preventing a perfect score.
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 has an output schema (which handles return values), a simple parameter structure, and no annotations, the description does a reasonably complete job. It covers purpose, usage guidance, and parameter constraints. The main gap is lack of behavioral details like error conditions or performance characteristics, but the output schema reduces the need for extensive description.
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?
The schema description coverage is 100%, so the schema already documents the single parameter thoroughly. The description adds minimal value beyond the schema by emphasizing 'absolute path, not a relative path' and mentioning the supported formats, but doesn't provide additional syntax or format details. This meets the baseline for high schema coverage.
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: converting specific file formats (PDF, Word, Excel, PPT) to Markdown format. It specifies the exact action ('convert') and resources (file types), making it unambiguous. With no sibling tools, differentiation isn't needed, so this is maximally clear.
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 explicit guidance: 'This is the optimal tool for reading such office files and should be prioritized for use.' It tells the agent when to use this tool (for reading office files) and gives a priority recommendation. However, it doesn't mention when NOT to use it or alternatives, which prevents a perfect score.
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. Dates show when Glama detected each change.
1 tool update
- First observed
parse_document_by_path
TDQS
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.
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