Htmlpdf Transform Mcp
Server Details
Htmlpdf Transform Mcp connects AI agents to real public APIs via MCP. Tools include
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- varvararatta/botfactory-mcp
- GitHub Stars
- 0
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Managed credentials
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Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Tool Definition Quality
Average 3.3/5 across 5 of 5 tools scored.
Each tool has a clearly distinct purpose: extracting tables, health check, converting HTML to markdown or text, and converting JSON to markdown table. No functional overlap.
Most tools follow a pattern (source_to_target or verb_noun), and all use snake_case. One exception: 'health_check' is a noun_noun instead of verb_noun, but it's a minor deviation.
With 5 tools, the count is reasonable for a focused server. It covers core HTML transformations, though PDF tools are missing from the name 'Htmlpdf'.
The server name implies both HTML and PDF handling, but there are no PDF-related tools. Significant gaps exist in the stated domain, limiting agents' ability to perform PDF operations.
Available Tools
5 toolsextract_tables_from_htmlBInspect
Extract all tables from HTML as structured data. Returns: {tables: [{headers, rows, row_count}]}
| Name | Required | Description | Default |
|---|---|---|---|
| html | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description must carry the burden. It discloses the return format (headers, rows, row_count) but does not mention behavior like error handling for missing tables or malformed HTML.
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 very concise, with one sentence and a clear return type definition. No wasted words, though it could be slightly more structured (e.g., listing use cases).
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 low complexity (1 parameter, no output schema), the description is minimally adequate. It specifies the return structure but lacks details on edge cases like no tables found or nested tables.
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 only parameter 'html' is a string, but the description does not add any meaning beyond the schema. With 0% schema description coverage, the description should clarify expected format, encoding, or size limits.
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 'extract' and the resource 'tables from HTML', distinguishing it from sibling tools like html_to_markdown and html_to_text. It specifies the output as structured data.
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 on when to use this tool versus alternatives. For example, it should mention that this is for extracting tables, while siblings handle other HTML conversions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
health_checkBInspect
Server health check.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose any behavioral traits beyond 'check'. It is assumed to be read-only, but lacks explicit confirmation of safety or side effects.
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 no wasted words. It is appropriately sized and front-loaded.
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 parameters and no output schema, the description is minimal but functional. However, it does not specify the return value (e.g., status, error details), which could aid an agent in interpreting results.
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?
There are no parameters, so the schema coverage is 100%. The description adds meaning by stating the tool checks server health, which is sufficient for a zero-parameter tool.
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 it's a server health check, which is a specific verb and resource. It is distinct from sibling tools that handle data extraction and conversion.
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 on when to use this tool versus alternatives. The purpose is implied, but there are no explicit context conditions or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
html_to_markdownBInspect
Convert HTML to clean Markdown. Returns: {markdown, original_length, markdown_length}
| Name | Required | Description | Default |
|---|---|---|---|
| html | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It mentions the return format ({markdown, original_length, markdown_length}), which adds some transparency, but lacks details on limitations, error handling, or input 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 short and front-loaded with the main purpose. It is efficient, though it could include more information without becoming verbose.
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 simplicity (one parameter, no output schema), the description is partially complete. It covers purpose and return structure but lacks usage guidelines and behavioral details.
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 0% description coverage and the description does not elaborate on the 'html' parameter beyond its existence. No format, size limits, or examples are given.
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 converts HTML to clean Markdown, which is a specific verb and resource. It distinguishes from sibling tools like 'extract_tables_from_html' and 'html_to_text'.
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 on when to use this tool versus alternatives. The description does not mention when not to use or provide context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
html_to_textAInspect
Strip all HTML tags and return clean plain text. Returns: {text, word_count}
| Name | Required | Description | Default |
|---|---|---|---|
| html | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully explains the transformation (strip HTML tags, return plain text and word count). It is straightforward but could note edge cases like scripts.
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?
Two sentences, front-loaded with action 'Strip all HTML tags', no wasted words.
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?
Sufficient for a simple tool: covers input purpose and output format. Could mention limitations like large input handling.
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 explains the single 'html' parameter's purpose (HTML to strip). Despite 0% schema description coverage, it adds essential meaning.
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 'strip' and resource 'HTML tags to plain text', distinguishing it from siblings like html_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?
No guidance on when to use this tool versus alternatives (e.g., html_to_markdown). The description simply describes the action without context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
json_to_markdown_tableCInspect
Convert list of dicts or list of lists to Markdown table. Returns: {table, rows, columns}
| Name | Required | Description | Default |
|---|---|---|---|
| data | Yes | ||
| headers | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Minimal behavioral disclosure; only mentions conversion and return fields. No annotations provided, so description should cover edge cases or side effects, but it does not.
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?
Extremely concise; essential information front-loaded. Every sentence adds value, no redundancy.
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 simple conversion tool with 2 params and no output schema, description provides basic functionality and return structure. Lacks examples or handling of edge cases, but sufficient for straightforward 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?
Description partially covers `data` parameter by specifying acceptable types (list of dicts or lists), but `headers` parameter is not explained. With 0% schema coverage, description partially compensates.
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?
Clearly states the tool converts lists to Markdown table. Distinguishes from sibling tools focused on HTML processing, but lacks elaboration on the output format.
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 on when to use or not use this tool versus alternatives. Missing context on prerequisites or constraints.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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