Skip to main content
Glama

Unphurl

by io.github.123Ergo

check_url

Read-onlyIdempotent

Check a single URL for security and data quality signals. Returns a risk score (0-100), detailed signal breakdown, and metadata.

Unphurl analyses URLs across seven dimensions: redirect behaviour, brand impersonation, domain intelligence (age, registrar, expiration, status codes, nameservers via RDAP), SSL/TLS validity, parked domain detection, URL structural analysis (length, path depth, subdomain count, entropy), and DNS enrichment (MX records). The score is calculated from these signals using either default weights or a custom scoring profile.

Higher scores mean more suspicious. The score is a signal, not a verdict. You decide the threshold based on the use case.

Billing: Most lookups are free. Known domains (Tranco Top 100K like google.com, github.com) return instantly with score 0 at no cost. Previously analysed domains return cached signals at no cost. Only unknown domains that run through the full analysis pipeline cost 1 pipeline check credit. The response's meta.pipeline_check_charged field tells you whether this check consumed a credit.

Use the "profile" parameter to score results with custom weights. For example, a "cold-email" profile might weight parked domains heavily while ignoring brand impersonation. Use list_profiles to see available profiles, or show_defaults to see all signal weights.

If the account has zero credits and the URL requires a full pipeline check, returns a 402 error with a link to purchase more credits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesThe URL to check (must be http:// or https://)
profileNoName of a custom scoring profile to use (optional). If omitted, default weights are used.

TDQS

A4.7/5.0
Behavior5/5

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

The description goes far beyond annotations by disclosing billing behavior (free vs. credit-charged lookups), the meta.pipeline_check_charged field, scoring dimensions, and the interpretive nature of the score ('a signal, not a verdict'). It also covers error handling (402) and caching semantics, which are valuable behavioral details.

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 well-structured and front-loaded with a summary sentence, followed by clear sections on scoring, billing, and usage. Every sentence adds meaningful information, and the length is justified by the tool's complexity. No filler or repetition.

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

Completeness5/5

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

Given the tool's complexity (multi-dimensional scoring, billing, custom profiles, error conditions) and lack of an output schema, the description provides a comprehensive picture. It covers return values, scoring dimensions, credit costs, response meta field, and 402 errors, making it sufficient for an AI agent to select and invoke the tool correctly.

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 the baseline is 3. The description adds value by explaining the profile parameter's purpose with a concrete example ('cold-email' profile) and clarifying that the url must be http/https. It also explains the billing implications of the url parameter, which enriches beyond the schema.

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?

The description clearly states the tool checks a single URL for security and data quality signals, distinguishing it from the sibling tool check_urls (plural) and other related tools. The verb 'Check' is specific and the resource (URL) and purpose (risk score) are explicit.

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

Usage Guidelines4/5

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

The description provides clear context for when to use the tool (single URL lookup) and references related tools like list_profiles and show_defaults for custom scoring. It does not explicitly compare against check_urls, but the 'single URL' phrasing implies the distinction. Billing and 402 error guidance helps with usage decisions.

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

All Unphurl toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.3/5.0
Disambiguation4/5

Most tools have clearly distinct purposes: check_url vs check_urls distinguish single vs batch, allowlist CRUD tools are separated, and profile management is distinct from account billing. Minor overlap exists between get_balance and get_stats (both report balance) and between list_profiles and show_defaults (both relate to scoring configuration), but descriptions clarify the differences.

Naming Consistency4/5

The vast majority of tools follow a verb_noun snake_case pattern (check_url, create_profile, list_allowlist, get_balance). A few outliers like purchase and signup are single verbs, but they are standard and do not break the overall predictability.

Tool Count4/5

18 tools is above the ideal 3-15 range but appropriate for the server's broad scope: URL analysis, custom scoring profiles, allowlist management, account billing, and reporting. Each tool serves a distinct function and none feel redundant or superfluous.

Completeness4/5

The tool surface covers the core domain thoroughly: single and batch URL checks, credit estimation, profile CRUD (create, list, delete, show defaults), allowlist CRUD, history, and account management (signup, balance, pricing, purchase). Minor gaps exist, such as no delete history or direct retrieval of a single past check by ID, but these are not critical.

Resources