URL / link safety check (bundle) — One call: SAFE/CAUTION/DANGER verdict for a URL — checks reachability & redirects, destination domain age, and hosting-IP reputation before an agent follows the link. Price: $0.05 USDC (Base, via x402).
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | http(s) URL to check |
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?
Annotations already declare readOnlyHint=true and destructiveHint=false, establishing that this is a safe, read-only operation. The description adds valuable behavioral context by specifying the verdict categories, the exact checks performed, and the pricing ($0.05 USDC via x402). It does not contradict the annotations.
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 compact, front-loaded sentence that packs the verdict type, the checks performed, the use case, and the price with no wasted words. Every clause adds useful information.
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 tool with one required parameter, no output schema, and read-only annotations, this description is complete: it tells the agent what it returns (SAFE/CAUTION/DANGER), what it checks, when to use it, and how much it costs. This is enough for an agent to decide whether and how to invoke it.
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 100% coverage: the 'url' parameter is already described as an 'http(s) URL to check.' The description mostly restates this with 'URL / link safety check' and 'link,' adding no deeper parameter semantics. Since schema coverage is high, the baseline of 3 is appropriate.
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 clearly identifies the tool as a URL/link safety check bundle that returns a SAFE/CAUTION/DANGER verdict, which is a specific verb+resource. It also lists the checks performed (reachability, redirects, domain age, hosting-IP reputation), making the purpose obvious. However, it does not explicitly distinguish itself from the sibling tool 'url_check', so its differentiation is not fully spelled out.
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 gives an explicit use case: 'before an agent follows the link.' This tells an agent when the tool is appropriate. It does not mention exclusions or name alternative tools, but the context is clear enough for someone with similar sibling tools to infer its usage.
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.
Many tools are clearly separated by prefix and data source, but several bundled products overlap heavily: vehicle_deal_check vs vehicle_report, realestate_property_report vs realestate_site_risk, finance_company_360 vs finance_health_scan, and domain_due_diligence vs email_domain_check/business_vet. An agent would frequently struggle to pick the correct premium bundle.
Tool names overwhelmingly follow a consistent snake_case category-prefix pattern like weather_, crypto_, vehicle_, finance_, and geo_. Minor deviations such as bare names (domain, ip) and noun-verb forms (dns_lookup, url_check) are easy to learn and don't create real confusion.
50 tools is far beyond the typical well-scoped 3–15 range and will require heavy filtering to navigate. The broad multi-domain data marketplace partially justifies the size, but it would be more coherent split into per-domain servers or consolidated further.
For a read-only data/diligence marketplace, the surface is quite comprehensive: weather, vehicle, crypto, SEC/finance, domain/email, sanctions, and geo workflows all have core operations plus fused verdict bundles. Minor gaps exist—such as a simple crypto price lookup or vehicle market value—but agents can usually work around them.