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Browser Screenshot

browser_screenshot

Capture a browser viewport, full page, or specific element as PNG or JPEG image for vision-capable AI models. Choose area and format to match your need.

Instructions

Take a screenshot and return it as an image (for vision-capable LLMs).

area: "viewport" (visible part), "full" (entire page), or "element" (requires ref). format: png or jpeg (jpeg is much smaller — prefer it for large pages).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
refNo
tabNo
areaNoviewport
formatNopng
qualityNo
sessionNodefault

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.0

TDQS

B3.3/5.0
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 of explaining behavior. It discloses the output type (image) and area/format behaviors, including that 'element' requires ref. It does not mention potential side effects, limitations on full-page captures, or how the image is returned (e.g., base64, path), but screenshot operations are inherently low-risk reads.

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 compact, front-loads the main action, and uses line breaks to separate parameter guidance. Every sentence adds useful information without filler or repetition of the schema.

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?

For the basic default use case, the description is sufficient: calling with no arguments will take a viewport screenshot in PNG. However, with 6 parameters, no output schema, and no annotation coverage, the description leaves important gaps around ref semantics, quality, session, and tab selection that an agent may need for correct advanced usage.

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%, so the description must compensate. It usefully explains 'area' and 'format' with values and trade-offs, but it leaves 'ref', 'tab', 'quality', and 'session' largely undocumented. 'ref' is only mentioned as 'requires ref' without defining what it should refer to, and 'quality' has no explanation at all.

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 and resource: 'Take a screenshot and return it as an image.' This is unambiguous and distinct from sibling extraction or navigation tools. However, it does not explicitly differentiate itself from browser_snapshot, which could be confused as an alternative visual capture.

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 description gives practical guidance on choosing area and format, including 'prefer it for large pages.' It also hints at the intended audience ('for vision-capable LLMs'). However, it does not explicitly state when to use this tool over alternatives like browser_snapshot or browser_extract_text.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.