Markdownify MCP Server - UTF-8 Enhanced
The Markdownify MCP Server - UTF-8 Enhanced converts various file types and web content into Markdown format, with enhanced UTF-8 support for multilingual content. You can:
Convert audio files to Markdown, including transcription if possible
Convert Bing search results pages to Markdown
Convert documents (DOCX, PDF, PPTX, XLSX) to Markdown
Convert images to Markdown, including metadata and description
Convert web pages to Markdown
Convert YouTube videos to Markdown, including transcript if available
Retrieve and process existing Markdown files by absolute path
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., "@Markdownify MCP Server - UTF-8 Enhancedconvert this Japanese PDF document to 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.
Markdownify MCP Server - UTF-8 Enhanced
This is an enhanced version of the original Markdownify MCP project, with improved UTF-8 encoding support and optimized handling of multilingual content.
Enhancements
Added comprehensive UTF-8 encoding support
Optimized handling of multilingual content
Fixed encoding issues on Windows systems
Improved error handling mechanisms
Related MCP server: MCP Markdown Conversion Server
Key Differences from Original Project
Enhanced Encoding Support:
Full UTF-8 support across all operations
Proper handling of Chinese, Japanese, Korean and other non-ASCII characters
Fixed Windows-specific encoding issues (cmd.exe and PowerShell compatibility)
Improved Error Handling:
Detailed error messages in both English and Chinese
Better exception handling for network issues
Graceful fallback mechanisms for conversion failures
Extended Functionality:
Added support for batch processing multiple files
Enhanced YouTube video transcript handling
Improved metadata extraction from various file formats
Better preservation of document formatting
Performance Optimizations:
Optimized memory usage for large file conversions
Faster processing of multilingual content
Reduced dependency conflicts
Better Development Experience:
Comprehensive debugging options
Detailed logging system
Environment-specific configuration support
Clear documentation in both English and Chinese
Features
Supports converting various file types to Markdown:
PDF files
Images (with metadata)
Audio (with transcription)
Word documents (DOCX)
Excel spreadsheets (XLSX)
PowerPoint presentations (PPTX)
Web content:
YouTube video transcripts
Search results
General web pages
Existing Markdown files
Quick Start
Clone this repository:
git clone https://github.com/JDJR2024/markdownify-mcp-utf8.git cd markdownify-mcp-utf8Install dependencies:
pnpm installNote: This will also install
uvand related Python dependencies.Build the project:
pnpm run buildStart the server:
pnpm start
Requirements
Node.js 16.0 or higher
Python 3.8 or higher
pnpm package manager
Git
Detailed Installation Guide
1. Environment Setup
Install Node.js:
Download from Node.js official website
Verify installation:
node --version
Install pnpm:
npm install -g pnpm pnpm --versionInstall Python:
Download from Python official website
Ensure Python is added to PATH during installation
Verify installation:
python --version
(Windows Only) Configure UTF-8 Support:
# Set system-wide UTF-8 setx PYTHONIOENCODING UTF-8 # Set current session UTF-8 set PYTHONIOENCODING=UTF-8 # Enable UTF-8 in command prompt chcp 65001
2. Project Setup
Clone the repository:
git clone https://github.com/JDJR2024/markdownify-mcp-utf8.git cd markdownify-mcp-utf8Create and activate Python virtual environment:
# Windows python -m venv .venv .venv\Scripts\activate # Linux/macOS python3 -m venv .venv source .venv/bin/activateInstall project dependencies:
# Install Node.js dependencies pnpm install # Install Python dependencies (will be handled by setup.sh) ./setup.shBuild the project:
pnpm run build
3. Verification
Start the server:
pnpm startTest the installation:
# Convert a web page python convert_utf8.py "https://example.com" # Convert a local file python convert_utf8.py "path/to/your/file.docx"
Usage Guide
Basic Usage
Converting Web Pages:
python convert_utf8.py "https://example.com"The converted markdown will be saved as
converted_result.mdConverting Local Files:
# Convert DOCX python convert_utf8.py "document.docx" # Convert PDF python convert_utf8.py "document.pdf" # Convert PowerPoint python convert_utf8.py "presentation.pptx" # Convert Excel python convert_utf8.py "spreadsheet.xlsx"Converting YouTube Videos:
python convert_utf8.py "https://www.youtube.com/watch?v=VIDEO_ID"
Advanced Usage
Environment Variables:
# Set custom UV path export UV_PATH="/custom/path/to/uv" # Set custom output directory export MARKDOWN_OUTPUT_DIR="/custom/output/path"Batch Processing: Create a batch file (e.g.,
convert_batch.txt) with URLs or file paths:https://example1.com https://example2.com file1.docx file2.pdfThen run:
while read -r line; do python convert_utf8.py "$line"; done < convert_batch.txt
Troubleshooting
Common Issues:
If you see encoding errors, ensure UTF-8 is properly set
For permission issues on Windows, run as Administrator
For Python path issues, ensure virtual environment is activated
Debugging:
# Enable debug output export DEBUG=true python convert_utf8.py "your_file.docx"
Usage
Command Line
Convert web page to Markdown:
python convert_utf8.py "https://example.com"Convert local file:
python convert_utf8.py "path/to/your/file.docx"Desktop App Integration
To integrate this server with a desktop app, add the following to your app's server configuration:
{
"mcpServers": {
"markdownify": {
"command": "node",
"args": [
"{ABSOLUTE_PATH}/dist/index.js"
],
"env": {
"UV_PATH": "/path/to/uv"
}
}
}
}Troubleshooting
Encoding Issues
If you encounter character encoding issues, ensure the
PYTHONIOENCODINGenvironment variable is set toutf-8Windows users may need to run
chcp 65001to enable UTF-8 support
Permission Issues
Ensure you have sufficient file read/write permissions
On Windows, you may need to run as administrator
Acknowledgments
This project is based on the original work by Zach Caceres. Thanks to the original author for their outstanding contribution.
License
This project continues to be licensed under the MIT License. See the LICENSE file for details.
Contributing
Contributions are welcome! Before submitting a Pull Request, please:
Ensure your code follows the project's coding standards
Add necessary tests and documentation
Update relevant sections in the README
Contact
For issues or suggestions:
Submit an Issue: https://github.com/JDJR2024/markdownify-mcp-utf8/issues
Create a Pull Request: https://github.com/JDJR2024/markdownify-mcp-utf8/pulls
Email: jdidndosmmxmx@gmail.com
Available Tools
10 toolsaudio-to-markdownC
Convert an audio file to markdown, including transcription if possible
| Name | Required | Description | Default |
|---|---|---|---|
| filepath | Yes | Absolute path of the audio file to convert |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool converts audio to markdown with transcription, but lacks details on permissions needed, rate limits, error handling, or what 'if possible' implies (e.g., supported formats, transcription accuracy). For a tool with no annotations, this leaves significant gaps in understanding its operation and constraints.
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 a single, efficient sentence that directly states the tool's function without unnecessary words. It is front-loaded with the core action ('Convert an audio file to markdown') and adds a useful qualifier ('including transcription if possible'). Every part earns its place, making it highly concise and well-structured.
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 complexity (audio processing and transcription) and lack of annotations and output schema, the description is incomplete. It doesn't explain return values (e.g., markdown content format), error cases, or behavioral details like supported audio formats. For a tool with no structured data to rely on, this leaves the agent under-informed about how to use it effectively.
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 description adds no parameter-specific information beyond what the input schema provides. The schema has 100% coverage with a clear description for 'filepath' as the 'Absolute path of the audio file to convert.' Since the schema does the heavy lifting, the baseline score of 3 is appropriate, as the description doesn't compensate with additional semantics like file format requirements or path examples.
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: 'Convert an audio file to markdown, including transcription if possible.' It specifies the verb ('convert'), resource ('audio file'), and outcome ('to markdown'), distinguishing it from siblings that convert other file types (e.g., pdf-to-markdown). However, it doesn't explicitly differentiate from siblings beyond the resource type, such as by noting unique features like audio-specific transcription.
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 no guidance on when to use this tool versus alternatives. It mentions 'including transcription if possible,' which hints at a capability, but doesn't specify prerequisites (e.g., file format support), exclusions, or direct comparisons to siblings like youtube-to-markdown for audio from videos. Without explicit when/when-not instructions, it leaves usage ambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
bing-search-to-markdownC
Convert a Bing search results page to markdown
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | URL of the Bing search results page |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the action ('Convert') but doesn't explain what the conversion entails (e.g., formatting, extraction of specific elements), potential errors (e.g., invalid URLs), or output characteristics (e.g., markdown structure). This leaves significant gaps in understanding the tool's behavior.
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 a single, efficient sentence with zero waste. It's front-loaded with the core action and resource, making it easy to parse quickly without unnecessary details.
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 lack of annotations and output schema, the description is incomplete. It doesn't address key aspects like what the markdown output includes (e.g., search results, metadata), error handling, or how it differs from sibling tools, leaving the agent with insufficient context for reliable use.
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%, with the parameter 'url' clearly documented in the input schema. The description doesn't add any additional meaning beyond this, such as URL format requirements or examples, but the schema provides adequate baseline information, justifying a score of 3.
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 verb ('Convert') and resource ('Bing search results page'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'webpage-to-markdown' or 'get-markdown-file', which could cause confusion about when to use this specific tool versus similar alternatives.
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?
No guidance is provided on when to use this tool versus alternatives. With siblings like 'webpage-to-markdown' that might handle general webpages, the description lacks context on prerequisites (e.g., requiring a Bing search URL) or exclusions, leaving the agent to guess based on the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
docx-to-markdownC
Convert a DOCX file to markdown
| Name | Required | Description | Default |
|---|---|---|---|
| filepath | Yes | Absolute path of the DOCX file to convert |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the conversion action but doesn't describe what happens during conversion (e.g., formatting preservation, error handling, output location, or performance characteristics). For a file conversion tool with zero annotation coverage, this leaves significant gaps in understanding the tool's behavior.
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 extremely concise—a single sentence with no wasted words. It is front-loaded with the core purpose, making it easy to scan and understand immediately. Every word earns its place by directly contributing to the tool's intent.
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 lack of annotations and output schema, the description is incomplete for a file conversion tool. It doesn't explain what the output is (e.g., markdown text, saved file), where it goes, or any limitations (e.g., file size, supported DOCX features). With siblings offering similar conversions, more context is needed to differentiate and use this tool effectively.
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%, with the single parameter 'filepath' well-documented in the schema. The description doesn't add any parameter-specific details beyond what the schema provides, such as file format requirements or conversion options. With high schema coverage, the baseline score of 3 is appropriate.
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 verb ('convert') and resource ('DOCX file to markdown'), making the purpose immediately understandable. It distinguishes from siblings by specifying the DOCX format, though it doesn't explicitly contrast with other conversion tools like pdf-to-markdown or pptx-to-markdown.
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 no guidance on when to use this tool versus alternatives. With multiple sibling tools for converting different formats to markdown (e.g., pdf-to-markdown, pptx-to-markdown), there is no indication of when DOCX conversion is appropriate or what distinguishes it from other conversion methods.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get-markdown-fileC
Get a markdown file by absolute file path
| Name | Required | Description | Default |
|---|---|---|---|
| filepath | Yes | Absolute path to file of markdown'd text |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the tool retrieves a file but doesn't disclose behavioral traits such as error handling (e.g., if file doesn't exist), permissions needed, rate limits, or output format. This leaves significant gaps for a tool that likely involves file system access.
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 a single, clear sentence with zero waste. It's front-loaded with the core action and resource, making it efficient and easy to understand without unnecessary details.
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 no annotations, no output schema, and a simple input schema, the description is incomplete. It doesn't cover key aspects like what happens on failure, the return format (e.g., raw markdown text or structured data), or how it differs from sibling tools, which are crucial for effective use.
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%, with the parameter 'filepath' fully documented in the schema as 'Absolute path to file of markdown'd text'. The description adds no additional meaning beyond this, such as examples or constraints, so it meets the baseline score of 3.
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 verb ('Get') and resource ('a markdown file'), specifying it retrieves content by absolute file path. However, it doesn't distinguish from sibling tools like 'audio-to-markdown' or 'webpage-to-markdown', which are conversion tools rather than retrieval tools, so it's not fully differentiated.
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?
No guidance is provided on when to use this tool versus alternatives. The description implies usage for retrieving existing markdown files, but it doesn't mention prerequisites (e.g., file must exist), exclusions (e.g., not for creating or converting files), or compare to siblings like 'docx-to-markdown' for conversion tasks.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
image-to-markdownC
Convert an image to markdown, including metadata and description
| Name | Required | Description | Default |
|---|---|---|---|
| filepath | Yes | Absolute path of the image file to convert |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that the conversion includes 'metadata and description,' which adds some context about output content. However, it fails to disclose critical behavioral traits such as error handling (e.g., for invalid file paths), performance aspects (e.g., processing time or size limits), or output format details. For a tool with no annotations, this is a significant gap.
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 extremely concise and front-loaded, consisting of a single sentence that directly states the tool's function. There is no wasted language or redundancy, making it efficient and easy to parse. Every word earns its place by conveying essential information.
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 complexity of file conversion and the lack of annotations and output schema, the description is incomplete. It does not explain what the markdown output includes beyond 'metadata and description,' such as formatting details or error cases. For a tool that performs a non-trivial operation with no structured output information, more context is needed to guide the agent effectively.
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 input schema has 100% description coverage, with the 'filepath' parameter clearly documented as 'Absolute path of the image file to convert.' The description does not add any meaning beyond this, as it does not elaborate on parameter usage or constraints. According to the rules, with high schema coverage (>80%), the baseline score is 3, which is appropriate here.
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 an image to markdown, including metadata and description. It specifies the verb ('convert') and resource ('image'), making it easy to understand. However, it does not explicitly differentiate from sibling tools like 'pdf-to-markdown' or 'webpage-to-markdown', which perform similar conversions on different file types, so it lacks sibling differentiation.
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 no guidance on when to use this tool versus alternatives. It does not mention any context, prerequisites, or exclusions, such as when to choose 'image-to-markdown' over other conversion tools like 'pdf-to-markdown' for different file formats. This leaves the agent without clear usage instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
pdf-to-markdownC
Convert a PDF file to markdown
| Name | Required | Description | Default |
|---|---|---|---|
| filepath | Yes | Absolute path of the PDF file to convert |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the conversion action but doesn't mention potential limitations (e.g., formatting accuracy, large file handling, error conditions), output details, or side effects. For a tool with zero annotation coverage, this leaves significant gaps in understanding how it behaves.
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 a single, efficient sentence with zero wasted words. It's front-loaded with the core action and resource, making it immediately understandable. This is an excellent example of conciseness in tool descriptions.
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 lack of annotations and output schema, the description is incomplete for a file conversion tool. It doesn't address output format details, error handling, or performance considerations, which are crucial for an agent to use it effectively. The simplicity of one parameter doesn't compensate for these omissions.
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%, with the single parameter 'filepath' fully documented in the schema as 'Absolute path of the PDF file to convert'. The description adds no additional parameter semantics beyond implying PDF file input, so it meets the baseline for high schema coverage without compensating value.
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 verb 'convert' and the resource 'PDF file to markdown', making the purpose unambiguous. It doesn't explicitly distinguish from siblings like 'docx-to-markdown' or 'pptx-to-markdown', but the PDF specificity is inherent. This is clear but lacks explicit sibling differentiation.
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 no guidance on when to use this tool versus alternatives. With siblings like 'docx-to-markdown' and 'webpage-to-markdown', there's no indication of prerequisites, file format requirements, or comparative use cases. It's a basic statement of function without contextual usage advice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
pptx-to-markdownC
Convert a PPTX file to markdown
| Name | Required | Description | Default |
|---|---|---|---|
| filepath | Yes | Absolute path of the PPTX file to convert |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the conversion action but lacks behavioral details: it doesn't mention if the tool overwrites files, requires specific permissions, handles errors, or outputs to a specific location. For a file conversion tool with zero annotation coverage, this is a significant gap in transparency.
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 a single, efficient sentence with zero waste: 'Convert a PPTX file to markdown'. It is front-loaded and appropriately sized, earning its place by clearly stating the core functionality without unnecessary elaboration.
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 complexity of file conversion (which involves input/output handling and potential errors), no annotations, and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., markdown text, file path), error conditions, or dependencies, leaving gaps for an AI agent to use it correctly.
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 input schema has 100% description coverage, with the 'filepath' parameter well-documented as 'Absolute path of the PPTX file to convert'. The description adds no additional parameter semantics beyond what the schema provides, so it meets the baseline of 3 for high schema coverage without extra value.
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 'Convert a PPTX file to markdown' clearly states the verb 'Convert' and the resource 'PPTX file', making the purpose immediately understandable. It distinguishes from siblings by specifying the PPTX format, though it doesn't explicitly differentiate from similar conversion tools like 'docx-to-markdown' beyond the file type.
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 no guidance on when to use this tool versus alternatives. With siblings like 'docx-to-markdown' and 'pdf-to-markdown', it doesn't specify scenarios where PPTX conversion is preferred or any prerequisites (e.g., file format compatibility). Usage is implied by the tool name but not articulated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
webpage-to-markdownC
Convert a webpage to markdown
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | URL of the webpage to convert |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the conversion action but lacks details on traits like error handling (e.g., invalid URLs, network issues), performance (e.g., timeouts, size limits), or output specifics (e.g., markdown format quality, included elements). This is a significant gap for a tool with no structured safety hints.
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 extremely concise—a single, direct sentence with zero wasted words. It's front-loaded with the core action, making it easy to parse quickly. Every word earns its place by conveying the essential purpose without fluff.
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 complexity (conversion operation), lack of annotations, and no output schema, the description is incomplete. It doesn't address behavioral aspects like what happens on failure, what the markdown output includes, or limitations (e.g., dynamic content handling). For a tool with no structured safety or output info, more context is needed.
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%, with the single parameter 'url' fully documented in the schema. The description adds no additional meaning beyond implying the URL is for a webpage, which is already clear from the schema. This meets the baseline score when the schema does the heavy lifting.
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 a specific verb ('Convert') and resource ('a webpage to markdown'), making it immediately understandable. However, it doesn't distinguish this tool from its siblings (e.g., 'pdf-to-markdown', 'docx-to-markdown'), which all convert different content types to markdown, so it doesn't reach the highest score.
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 no guidance on when to use this tool versus alternatives. It doesn't mention any prerequisites (e.g., URL accessibility), exclusions (e.g., unsupported webpage types), or comparisons to sibling tools like 'bing-search-to-markdown' for web content. This leaves the agent with minimal context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
xlsx-to-markdownC
Convert an XLSX file to markdown
| Name | Required | Description | Default |
|---|---|---|---|
| filepath | Yes | Absolute path of the XLSX file to convert |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool converts files but doesn't explain how the conversion works, what happens to the original file, or any limitations like file size or formatting issues. This leaves key behavioral traits unspecified.
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 extremely concise—just one sentence—and front-loaded with the core action. There's no wasted language, making it easy to parse quickly. This efficiency is ideal for a simple tool.
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 lack of annotations and output schema, the description is incomplete. It doesn't cover behavioral aspects like conversion quality or error handling, and with no output schema, it fails to explain what the markdown output looks like. For a conversion tool, this leaves significant gaps in understanding.
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 input schema has 100% description coverage, with the 'filepath' parameter clearly documented. The description doesn't add any extra meaning beyond the schema, such as examples or constraints, but since the schema is comprehensive, a baseline score of 3 is appropriate.
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 XLSX files to markdown format. It specifies the verb 'convert' and the resource 'XLSX file', making it easy to understand. However, it doesn't explicitly differentiate from sibling tools like 'docx-to-markdown' or 'pdf-to-markdown' beyond the file type, which keeps it from a perfect score.
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 no guidance on when to use this tool versus alternatives. It doesn't mention any prerequisites, such as file format requirements or when other conversion tools might be more appropriate. This lack of context makes it harder for an AI agent to choose correctly among the many sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
youtube-to-markdownC
Convert a YouTube video to markdown, including transcript if available
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | URL of the YouTube video |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but offers minimal behavioral insight. It mentions transcript inclusion 'if available', hinting at conditional behavior, but lacks details on error handling, rate limits, authentication needs, or output format beyond markdown.
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 a single, efficient sentence with zero waste. It's front-loaded with the core purpose and includes a useful qualifier about transcripts, making it appropriately concise.
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?
For a tool with no annotations and no output schema, the description is incomplete. It doesn't explain what the markdown output contains (e.g., structure, metadata), potential errors, or dependencies like internet access, leaving significant gaps for agent usage.
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 'url' parameter fully. The description adds no additional parameter semantics beyond implying the URL must be for a YouTube video, which is minimal value over the schema.
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 verb 'convert' and the resource 'YouTube video to markdown', specifying it includes transcript if available. It distinguishes from siblings by focusing on YouTube specifically, though it doesn't explicitly contrast with other conversion tools.
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?
No guidance is provided on when to use this tool versus alternatives like 'audio-to-markdown' or 'webpage-to-markdown'. The description implies usage for YouTube videos but doesn't mention prerequisites, limitations, or comparative advantages.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
TDQS
Every tool has a clearly distinct purpose based on the input source type (audio, Bing search, DOCX, file, image, PDF, PPTX, webpage, XLSX, YouTube). There is no overlap or ambiguity—each tool handles a specific format or source, making it easy for an agent to select the correct one based on the input.
All tool names follow a consistent pattern: [source]-to-markdown or get-markdown-file, using snake_case throughout. This predictable naming scheme (e.g., audio-to-markdown, pdf-to-markdown) makes the tools easy to understand and navigate, with no deviations in style.
With 10 tools, the server is well-scoped for its purpose of converting various formats to markdown. Each tool earns its place by covering a distinct input type, providing comprehensive coverage without being overwhelming or sparse for the domain.
The tool surface is complete for the server's purpose of markdown conversion, covering a wide range of common input sources (audio, documents, images, web content, videos). There are no obvious gaps; agents can handle diverse conversion tasks without dead ends or missing operations.
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