render_screenshot
Captures rendered webpage screenshot image data ($0.01 USDC)
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes |
I used the same url for two different postings.
Captures rendered webpage screenshot image data ($0.01 USDC)
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It mentions the page is 'rendered' and notes the cost, but does not describe output format, execution behavior, potential failures, or any side effects. This is thin behavioral context for an operation that produces image data.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence with no filler. The verb and resource are front-loaded, and the cost detail is included without distracting from the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter tool, the description is mostly adequate, but it leaves ambiguity about the output format (e.g., PNG, JPEG, base64) and whether any URL restrictions apply. The missing output schema means these details should have been in the description; an agent cannot reliably know how to consume the 'screenshot image data' result.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description must compensate for the undocumented 'url' parameter. It adds the context that the URL refers to a 'webpage', but it does not specify expected URL format, accessibility requirements, or what constitutes a valid input. The parameter name is self-explanatory enough to reach a baseline, but no additional semantics are provided.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Captures') and a concrete resource ('rendered webpage screenshot image data'), making the tool's basic function immediately clear. It inherently differentiates itself from content-scraping siblings, though it does not explicitly name or contrast them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 web_scraper or browser_scraper. There is no mention of suitability conditions, exclusions, or selection criteria, leaving the agent to infer usage purely from the tool's name and function.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Several tools cluster around web content retrieval: web_scraper, browser_scraper, extract_json, and render_screenshot all pull from web pages and could be confused. data_feeds and public_data_feed also sound similar. Most other tools have distinct purposes, but these overlapping clusters create real selection ambiguity.
Tool names mix verb-led conventions like deploy_contract, extract_json, and render_screenshot with noun-led names like browser_scraper, pdf_extractor, and smart_contract_verifier. Pairs such as web_scraper vs browser_scraper and extract_json vs pdf_extractor are also stylistically inconsistent.
Twelve tools is a reasonable count for a paid gateway offering data extraction, feeds, and contract deployment. However, the scraping/extraction cluster is somewhat redundant, so the set could be tightened without losing much functionality.
The toolset broadly covers web data extraction, PDF processing, feeds, Base/Solana contract deployment, and blockchain analytics. Notable gaps include the lack of Solana-side balance/analytics tools and any post-deployment contract interaction or management capability.