browser_scraper
Unblockable JS-rendering browser scraper ($0.005 USDC)
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes |
Unblockable JS-rendering browser scraper ($0.005 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. It does add useful behavioral facts: the tool renders JavaScript, claims to bypass blocking, and costs $0.005 USDC per call. However, it does not disclose return format, timeout behavior, rate limits, or whether the operation is read-only, leaving significant gaps.
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, dense phrase with no filler. The price is a distinct and useful detail, and the key capabilities are front-loaded. It is appropriately sized for the tool's simplicity, even though brevity sacrifices depth.
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?
Given a simple schema with one required parameter and no output schema, the description covers the core identity, cost, and key capability. It is incomplete in that it never states what the returned output is and does not mention alternatives, but for a low-complexity scraper it is minimally viable.
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?
The input schema has a single required 'url' string with no description, and schema description coverage is 0%. The description does not mention the URL parameter or clarify expected format, so it fails to compensate for the missing schema documentation. The self-explanatory property name 'url' is the only reason this is not a 1.
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 identifies the tool as a browser-based scraper with JS rendering and anti-blocking capabilities, and includes pricing. However, it is a noun phrase rather than a statement of action, and it does not explicitly differentiate from the sibling web_scraper. It is more informative than a bare tautology but still vague about the exact operation.
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?
There is no explicit statement of when to use this tool over alternatives; the features 'Unblockable' and 'JS-rendering' imply it is meant for dynamic or protected pages, but no exclusions or alternative conditions are given. The sibling list reveals a web_scraper exists, yet the description does not route between them.
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.
The tools are largely distinct, but web_scraper and browser_scraper overlap on web page scraping, and data_feeds and public_data_feed are hard to distinguish without more detail. A few descriptions do help separate output formats, but an agent could still misfire.
All names use snake_case and are descriptive, but the naming pattern is mixed: deploy_contract and render_screenshot are verb-first, while smart_contract_verifier, base_analytics, and data_feeds are noun phrases. This prevents a predictable verb_noun convention.
Twelve tools is a reasonable count and each has a defined paid purpose. However, the set spans scraping, data feeds, DeFi yields, and smart-contract deployment, so it feels slightly broad for a single server.
Core operations exist for scraping, extraction, deployment, verification, and data feeds, but the surface is incomplete for lifecycle workflows: contracts can be deployed but not called/managed, and data feeds cannot be listed or refreshed. The gaps are noticeable but not fatal for independent one-off API calls.