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@rendershot/mcp-server

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by Rendershot

generate_pdf

Convert a web page or HTML content into a PDF document. Returns the PDF as a base64-encoded string for direct use.

Instructions

Generate a PDF from a web page or HTML content. Returns the PDF as a base64-encoded string.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNoURL of the page to render. Exactly one of url or html is required.
htmlNoRaw HTML to render. Exactly one of url or html is required.
formatNoPaper size.A4
orientationNoPage orientation.portrait
print_backgroundNoPrint background graphics and colors.
wait_forNoWhen to consider the page loaded: load | dom_content_loaded | network_idle | commit | CSS selector.dom_content_loaded
delay_msNoExtra delay in milliseconds after page load before capturing.
ai_cleanupNoRemove cookie banners/popups before capture. 'fast' uses JS heuristics (1 credit). 'thorough' adds an LLM pass (3 credits; requires Anthropic key on the server).
headersNoCustom HTTP headers to send with the render request. Use for Bearer tokens, X-Tenant-Id, etc. Host / Cookie / Content-Length / Sec-* / Connection are rejected server-side. Max 30 headers, values ≤ 2 KB.
cookiesNoSession cookies to inject before page navigation. Each cookie needs either 'domain' or 'url'. Max 50 per request.
basic_authNoHTTP Basic auth credentials. Forwarded to the headless browser on a 401 challenge.
output_pathNoAbsolute or relative path to save the PDF file (e.g. /tmp/invoice.pdf). If omitted, the PDF is returned as base64 in the response.
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. It mentions the basic output format (base64) but omits important details such as maximum page size, render timeouts, or that the 'ai_cleanup' parameter consumes credits. The description lacks transparency about side effects or constraints.

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 very concise: two sentences that front-load the core functionality. No unnecessary words or repetition.

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 (12 parameters, enums, nested objects, no output schema, no annotations), the description is too sparse. It fails to explain return values when 'output_path' is omitted, credit costs, or error conditions. A more complete description would include these details.

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 description does not need to add much. The description only restates the tool's purpose and does not elaborate on parameter meaning beyond what the schema already provides. This meets the baseline for high 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 function: generate a PDF from a web page or HTML and returns it as base64. While it distinguishes from siblings like 'take_screenshot' (different output format) and 'check_balance' (unrelated), it does not explicitly differentiate from 'bulk_render' which may have overlapping functionality.

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 like 'bulk_render' or 'take_screenshot'. It does not mention prerequisites, limitations, or context for choosing one tool over another.

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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