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Precision PDF MCP Server

Precision PDF MCP Server

by zuan412
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

hpe_render_clean_verify

Render the completed PDF page to a high-resolution PNG for visual QA, verifying answers before submission without grids or badges.

Instructions

Render the final, clean PDF page (with answers, WITHOUT any grid or badges) to a high-resolution PNG image for visual QA before submission.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "pdf_path": "<pdf_path>",
      "page_number": "<page_number>"
    },
    "name": "hpe_render_clean_verify"
  }
}

Input Schema

NameRequiredDescriptionDefault
dpiNo
pdf_pathYes
page_numberYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the burden. It usefully discloses the rendered content (answers rendered, grid and badges omitted) and output format/resolution, but says nothing about side effects, overwriting an existing image, or where the PNG is written. For a render/QA tool the risk is low, but the disclosure is partial.

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?

A single, front-loaded sentence with the key constraint (no grid or badges) placed early. The parenthetical is slightly cumbersome but earns its place by disambiguating the output content; nothing redundant remains.

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?

With an output schema present, return values need not be described, and calling this tool is straightforward. Still, three parameters at 0% coverage and no annotation coverage means the definition is only minimally complete for anything beyond the happy path.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% and the description compensates for none of it: dpi (default 150) is only hinted at via 'high-resolution', and pdf_path and page_number are never explained (no path format, no zero-vs-one-based page numbering). An agent must guess the relationship between 'high-resolution' and the default dpi 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?

States a specific verb and resource chain: render a PDF page to a high-resolution PNG. The parenthetical '(with answers, WITHOUT any grid or badges)' implicitly distinguishes it from the sibling hpe_render_verify, but the sibling is never named, so the differentiation is inferential rather than explicit.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'for visual QA before submission' gives a clear purpose and timing cue, which is useful context. However, it never states when to prefer this over hpe_render_verify or the inspect_* tools, leaving the agent to infer the alternative from the word 'clean'.

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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