A
license-
qualityD
maintenanceMCP Server for Markdown to PDF conversion.
Last updated
MIT
Pdfrender
Server Details
HTML-to-PDF MCP server — render pixel-faithful PDFs from HTML.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- getpdfrender/pdfrender
- GitHub Stars
- 0
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Tool Definition Quality
A4.5/5.0
Tool DescriptionsA
Average 4.7/5 across 1 of 1 tools scored.
Server CoherenceA
Disambiguation5/5
Only one tool exists, so there is no possibility of confusion with other tools.
Naming Consistency5/5
The single tool 'render_html_to_pdf' follows a clear verb_noun pattern, which is consistent despite there only being one tool.
Tool Count3/5
A single tool for a PDF rendering server is borderline; while it covers the core functionality, the tool count is thin for typical servers.
Completeness3/5
The tool handles HTML to PDF rendering but imposes a 256 KB size limit, directing larger documents to the REST API—a notable gap in the server's own tool surface.
Available Tools
1 toolrender_html_to_pdfAInspect
Render an HTML document to a PDF, returned base64-encoded.
html is a complete HTML string. Inline any images, fonts and CSS as
data: URIs — external http(s) resources are not fetched, and no
JavaScript is executed (HTML + CSS only). Returns
{"pdf_base64": "<base64-encoded PDF>", "pages": <page count>}.
Costs one credit. For documents larger than 256 KB, use the REST API
(POST /v1/render).
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| html | Yes |
Output Schema
ParametersJSON Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
A4.7/5.0
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden and delivers thoroughly: no external resource fetching, no JavaScript execution, base64 output with page count, and credit cost. All behavioral traits are disclosed, making it transparent for an agent.
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 relatively concise with 4 sentences covering purpose, parameter detail, limitations, return format, cost, and alternative. Each sentence adds value, though it could be slightly more structured (e.g., bullet points). It is front-loaded with the core action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with 1 parameter and an output schema, the description covers input format, constraints, output structure (including return fields), cost, and fallback for large docs. It leaves no significant gaps: the agent knows exactly what to expect and when to avoid the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema only defines 'html' as a string with no description (0% coverage). The description compensates excellently by specifying it must be a complete HTML string and advising to inline resources as data: URIs. This adds essential meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Render an HTML document to a PDF, returned base64-encoded.' The verb 'Render' and the resource 'HTML document to a PDF' are specific and unambiguous. There are no sibling tools, so no differentiation needed, but the purpose is well-defined.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidelines on when not to use this tool: for documents larger than 256 KB, it recommends the REST API. It also lists limitations (no external resources, no JavaScript) and mentions the cost (one credit). This is strong guidance, though it lacks a positive 'when to use' statement for typical cases.
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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