Markdownify MCP Server

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v0.0.2
Disambiguation5/5
Every tool has a clearly distinct purpose focused on converting a specific input type (audio, Bing search, DOCX, etc.) to markdown. There is no ambiguity or overlap in functionality—each tool targets a unique source format, making tool selection straightforward for an agent.
Naming Consistency5/5
All tool names follow a consistent pattern of 'source-to-markdown' (e.g., audio-to-markdown, docx-to-markdown). This uniform verb_noun style is predictable and readable, with no deviations in naming conventions across the set.
Tool Count5/5
With 10 tools, the server is well-scoped for its purpose of converting various file types and sources to markdown. Each tool earns its place by covering a distinct input format, and the count is neither too sparse nor overwhelming for the domain.
Completeness5/5
The tool set provides comprehensive coverage for converting common file types (DOCX, PDF, PPTX, XLSX, image, audio) and sources (webpage, YouTube, Bing search) to markdown. There are no obvious gaps—it supports a complete workflow for markdown conversion from diverse inputs.
Average 2.9/5 across 10 of 10 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
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 'including transcription if possible', which hints at conditional behavior, but fails to detail critical aspects like error handling, processing time, audio format limitations, or output structure. This leaves significant gaps in understanding how the tool behaves in practice.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded in a single sentence, efficiently stating the core function without unnecessary details. However, the phrase 'if possible' introduces ambiguity that could be clarified with slightly more context, slightly reducing efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of audio processing and lack of annotations or output schema, the description is incomplete. It omits essential context like supported audio formats, transcription accuracy, output format details, or error conditions. For a tool with no structured behavioral hints, this leaves the agent under-informed about how to effectively use it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, clearly documenting the single parameter 'filepath'. The description adds no additional parameter semantics beyond what the schema provides, such as file size limits or supported audio formats. Since schema coverage is high, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function with a specific verb ('convert') and resource ('audio file'), and the target format ('markdown') is explicit. However, it doesn't distinguish itself from sibling tools like 'youtube-to-markdown' or 'webpage-to-markdown' beyond the input type, missing explicit differentiation in scope or capabilities.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 lacks context such as prerequisites (e.g., file format support), performance expectations, or comparisons to siblings like 'youtube-to-markdown' for audio from videos, leaving the agent to infer usage 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.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. While 'convert' implies a transformation operation, the description doesn't disclose important behavioral traits like whether authentication is needed, rate limits, what specific elements get converted (just text? images? links?), or error conditions. This leaves significant gaps in understanding how the tool actually behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise and front-loaded with the core functionality. The single sentence efficiently communicates what the tool does without any wasted words or unnecessary elaboration, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
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 insufficiently complete. For a conversion tool with no structured output documentation, the description should at minimum indicate what gets returned (markdown format? structure? what elements are included?). The absence of behavioral context and output information makes this inadequate for proper tool understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema description coverage, the input schema already fully documents the single 'url' parameter. The description doesn't add any meaningful parameter semantics beyond what's in the schema - it doesn't clarify URL format requirements, whether the URL must be a specific Bing search results format, or any constraints on the input URL.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 ('Bing search results page'), making it immediately 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 alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 markdown conversion tools available (like 'webpage-to-markdown' and 'get-markdown-file'), there's no indication of when this specific Bing-focused tool is appropriate versus general webpage conversion tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 omits critical details: whether it's read-only or destructive (e.g., modifies the original file), error handling (e.g., invalid files), performance traits (e.g., speed), or output specifics (e.g., markdown format details). This leaves significant gaps for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise and front-loaded with a single, clear sentence: 'Convert a DOCX file to markdown'. There is zero waste, making it efficient for quick understanding without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (a file conversion operation), lack of annotations, and no output schema, the description is incomplete. It fails to address behavioral aspects (e.g., safety, errors), usage context, or output details, leaving the agent with insufficient information to invoke the tool confidently beyond the basic action.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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. With 100% schema description coverage, the schema fully documents the single parameter ('filepath'), so the baseline is 3. The description doesn't compensate with additional context 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.
Purpose4/5
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 a DOCX file to markdown' specifies the verb (convert) and resource (DOCX file) with the target format (markdown). However, it doesn't distinguish from sibling tools like 'pptx-to-markdown' or 'pdf-to-markdown' beyond the input file type, missing explicit differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 lacks context such as prerequisites (e.g., file must exist), exclusions (e.g., not for other formats), or comparisons to siblings like 'pdf-to-markdown', leaving the agent to infer usage based on file type alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only states the basic operation. It lacks behavioral details such as error handling (e.g., if file doesn't exist), output format (e.g., raw markdown text), or performance considerations like file size limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
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 and appropriately sized for a simple tool, earning its place by clearly stating the core functionality.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read operation with no annotations and no output schema, the description is incomplete. It doesn't explain what is returned (e.g., file content, metadata) or address potential issues like file access errors, leaving gaps in understanding tool behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents the single parameter. The description adds no additional meaning beyond implying the file must be in markdown format, which is minimal value over the schema's 'Absolute path to file of markdown'd text'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and resource ('a markdown file'), specifying it retrieves content by absolute file path. It distinguishes from sibling tools that convert various formats to markdown rather than retrieving existing files, though it doesn't explicitly name alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. While siblings are conversion tools, the description doesn't mention this distinction or specify prerequisites like file existence or permissions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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. While 'convert' implies a transformation operation, the description doesn't disclose important behavioral traits such as whether the conversion is lossy, what markdown format is produced, whether it handles scanned PDFs with OCR, or any error conditions. This leaves significant gaps in understanding how the tool behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at just 5 words, with zero wasted language. It's front-loaded with the core purpose and contains no unnecessary information, making it efficient for quick understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of file format conversion and the lack of both annotations and output schema, the description is insufficiently complete. It doesn't explain what the tool returns (e.g., markdown text, file path to converted content), doesn't mention limitations or requirements, and provides no context about the conversion quality or supported PDF features.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with the single parameter 'filepath' clearly documented as requiring an absolute path. The description doesn't add any meaningful parameter semantics beyond what the schema already provides, so it meets the baseline score of 3 for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as converting a PDF file to markdown, which is a specific verb (convert) and resource (PDF file). It distinguishes itself from siblings by focusing on PDF files specifically, though it doesn't explicitly contrast with other conversion tools like docx-to-markdown or image-to-markdown.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 file types to markdown (e.g., docx-to-markdown, image-to-markdown), there's no indication of when PDF 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.
Behavior2/5
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 omits critical details such as error handling for invalid files, output format specifics, performance expectations, or any side effects. This is inadequate for a tool with no annotation support.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste—it directly states the tool's function without unnecessary words. It is appropriately sized and front-loaded, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of file conversion, lack of annotations, and no output schema, the description is incomplete. It fails to address output format, error cases, or behavioral traits, leaving significant gaps for an agent to operate effectively. This is particularly problematic in a server with multiple similar tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 adds no additional parameter semantics beyond implying the input must be a PPTX file, which is redundant with the tool name. Baseline 3 is appropriate as the schema handles the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 'PPTX file to markdown', making the purpose immediately understandable. It distinguishes from siblings by specifying PPTX format, though it doesn't explicitly contrast with other conversion tools like 'docx-to-markdown' or 'pdf-to-markdown'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 multiple sibling conversion tools (e.g., docx-to-markdown, pdf-to-markdown), the description lacks context on file format suitability, prerequisites, or comparisons, leaving the agent to infer usage based on file extension alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 action ('convert') but does not disclose behavioral traits such as rate limits, authentication needs, error handling (e.g., for invalid URLs), or output specifics (e.g., formatting quality). This leaves significant gaps for a tool that likely involves web requests and content parsing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It is front-loaded with the core action and resource, making it easy to parse. Every word earns its place by conveying essential information without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of web conversion (involving network calls, HTML parsing, and markdown generation), the description is incomplete. No annotations exist, and there is no output schema to clarify return values or errors. The description lacks details on limitations (e.g., JavaScript-rendered pages), making it inadequate for informed tool selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with the 'url' parameter fully documented. The description adds no additional meaning beyond what the schema provides (e.g., URL format constraints or examples). With high schema coverage, the baseline score of 3 is appropriate, as the description does not compensate but also does not detract.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Convert a webpage to markdown' clearly states the verb ('convert') and resource ('webpage'), specifying the output format ('markdown'). It distinguishes from siblings like 'audio-to-markdown' or 'pdf-to-markdown' by specifying the input source ('webpage'), but does not explicitly differentiate beyond the input type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 prerequisites (e.g., URL accessibility), exclusions (e.g., dynamic vs. static pages), or comparisons to siblings like 'bing-search-to-markdown' for search results. Usage is implied by 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.
Behavior2/5
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 critical details like whether the tool modifies the original file, requires specific permissions, handles errors (e.g., invalid file formats), or outputs to a specific location. For a file-processing tool with zero annotation coverage, 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with zero wasted words. It's front-loaded with the core action and resource, making it highly efficient and easy to parse, which is ideal for quick tool selection by an AI agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
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 markdown output looks like (e.g., table formatting for spreadsheets), error handling, or dependencies, leaving the agent with insufficient context for reliable invocation despite the simple parameter schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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' well-documented in the schema as 'Absolute path of the XLSX file to convert'. The description adds no additional parameter semantics beyond what the schema provides, so it meets the baseline score 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.
Purpose4/5
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 'XLSX file to markdown', making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'docx-to-markdown' or 'pdf-to-markdown' beyond specifying the input format, missing an opportunity to highlight unique aspects of XLSX conversion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 '*-to-markdown' siblings available, it doesn't specify scenarios where XLSX conversion is appropriate (e.g., for spreadsheet data) or when other tools might be better suited, leaving the agent to infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 the output includes 'metadata and description,' hinting at what the tool returns, but lacks details on error handling, performance (e.g., processing time), or limitations (e.g., file size constraints). For a tool with no annotations, this is insufficient to fully inform the agent about its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence: 'Convert an image to markdown, including metadata and description.' It is front-loaded with the core purpose and avoids unnecessary words, making it highly concise and well-structured for quick understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (conversion with metadata), no annotations, and no output schema, the description is minimally adequate. It specifies the input (image) and output (markdown with metadata), but lacks details on output structure, error cases, or integration context. This leaves gaps that could hinder effective use by an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 adds no additional parameter semantics beyond this, such as format requirements or examples. Given the high schema coverage, a baseline score of 3 is appropriate, as the schema handles the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 image to markdown, including metadata and description.' It specifies the verb ('convert'), resource ('image'), and output format ('markdown'), distinguishing it from sibling tools like 'audio-to-markdown' or 'pdf-to-markdown' by focusing on images. However, it doesn't explicitly differentiate from similar tools beyond naming, keeping it at a 4 rather than a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 prerequisites (e.g., file accessibility), exclusions (e.g., unsupported image formats), or comparisons to sibling tools like 'webpage-to-markdown' for different content types. This lack of context leaves the agent to infer usage based on the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 'including transcript if available,' which hints at conditional behavior, but doesn't explain what happens if no transcript is available, error handling, rate limits, or authentication needs. For a conversion tool with zero annotation coverage, this leaves significant gaps in understanding its operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
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's front-loaded with the core action and includes a useful detail about transcripts. Every part of the sentence 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.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (conversion with conditional transcript inclusion), lack of annotations, and no output schema, the description is minimally adequate. It covers the basic purpose but misses details like output format specifics, error cases, or performance expectations. It's complete enough to understand the tool's intent but lacks depth for reliable agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the parameter 'url' fully documented in the schema as 'URL of the YouTube video.' The description doesn't add any additional meaning beyond this, such as URL format examples or constraints. Given the high schema coverage, a baseline score of 3 is appropriate, as the schema handles the parameter documentation adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 a YouTube video to markdown, including transcript if available.' It specifies the verb ('Convert'), resource ('YouTube video'), and output format ('markdown'), which is clear and actionable. However, it doesn't explicitly differentiate from sibling tools like 'audio-to-markdown' or 'webpage-to-markdown' beyond the resource type, keeping 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.
Usage Guidelines2/5
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 sibling tools, prerequisites (e.g., video accessibility), or exclusions (e.g., for non-YouTube URLs). Usage is implied by the name and description alone, with no explicit context or alternatives provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

GitHub Badge

Glama performs regular codebase and documentation scans to:

Confirm that the MCP server is working as expected.
Confirm that there are no obvious security issues.
Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

Copy to your README.md:

[![markdownify-mcp MCP server](https://glama.ai/mcp/servers/BartoseLudwiczuk/markdownify-mcp/badges/card.svg)](https://glama.ai/mcp/servers/BartoseLudwiczuk/markdownify-mcp)

Score Badge

Copy to your README.md:

[![markdownify-mcp MCP server](https://glama.ai/mcp/servers/BartoseLudwiczuk/markdownify-mcp/badges/score.svg)](https://glama.ai/mcp/servers/BartoseLudwiczuk/markdownify-mcp)

Latest Blog Posts

Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)
By Om-Shree-0709 on July 25, 2026.
mcp
Agent Identity
OAuth 2.1
Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/BartoseLudwiczuk/markdownify-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server