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Glama

Read a page as markdown

read_url

Render a URL in a real headless browser (JavaScript executed) and return clean, LLM-ready markdown. Use this when fetch() gives you an empty shell or a bot wall. Paid: call without x_payment to receive this call's exact terms (amount, asset, network), sign them, then call again with x_payment. The free pricing tool lists every price at once.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesAbsolute URL to read.
x_paymentNoOptional signed x402 payment payload (base64, what the X-PAYMENT header carries). Omit to receive the exact payment terms; sign them (e.g. @x402/fetch) and call again with this argument to settle and get the data.

TDQS

A4.6/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses the headless browser behavior (JavaScript executed) and the two-step payment flow (call without x_payment to get terms, then call again with signed payload). It does not mention potential failure modes, but the disclosures are significant and well-integrated.

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-loaded with the core purpose, then provides usage guidance and payment details. Every sentence earns its place; no filler or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations and no output schema, the description covers key aspects: what it does (renders JS, returns markdown), when to use it, and the payment mechanism. It does not explain all edge cases or error handling, but for a tool with a clear return type and payment flow, it is sufficiently complete.

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

Parameters4/5

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

Schema coverage is 100%, so parameters are already well-documented. The description adds value by explaining the payment protocol's two-step process, which the schema only hints at. It also clarifies the purpose of x_payment in the flow, exceeding what the bare schema provides.

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?

States a specific verb ('Render') and resource ('a URL in a real headless browser'), clearly distinguishing the tool from siblings like screenshot_url by focusing on markdown output. The purpose is unambiguous and actionable.

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

Usage Guidelines5/5

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

Explicitly tells when to use: 'Use this when fetch() gives you an empty shell or a bot wall.' Also references the sibling 'pricing' tool for payment terms, providing clear context for how this tool fits among alternatives.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.4/5.0
Disambiguation5/5

Each tool serves a clearly distinct function—data discovery, holidays, icons, OCR, news, PDF extraction, pricing, URL reading, data requests, screenshots, timezone, and weather. There is no overlap in purpose; even read_url and screenshot_url differ by output format (markdown vs PNG).

Naming Consistency4/5

All tool names use lowercase snake_case and are readable, but the pattern is not uniformly verb_noun—some are nouns (holidays, news, pricing, timezone, weather) while others are verb_noun (find_data, read_url). This is a minor inconsistency that doesn't impede predictability.

Tool Count5/5

With 12 tools, the server sits comfortably within the ideal 3–15 range. Each tool earns its place covering a distinct web utility, and the count matches the broad but well-defined scope of a general-purpose web toolbox.

Completeness4/5

The tool surface is fairly complete for a general-purpose web utility server, covering common tasks like fetching, extracting, searching, and checking time/weather/holidays, plus meta tools (pricing, request_data). Minor gaps like a generic text summarizer or video tool exist, but nothing critical for the intended purpose.

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