Skip to main content
Glama
ScamVerify

ScamVerify

by scamverifyai

Related Servers

Alternatives to ScamVerify

No user-submitted related servers found.

    Related Servers

    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables AI agents and apps to check URLs, domains, IP addresses, phone numbers, emails, crypto wallets, IBANs, mobile apps, and payment handles for scam, phishing, and fraud risk, returning verdicts, probabilities, facts, and reason codes.
      MIT
    • F
      license
      Not graded
      quality
      A
      maintenance
      Enables phone number intelligence and spam-risk detection by combining metadata, FTC complaint history, and IPQS reputation into explainable risk scores with confidence levels.
      1
      -
    • A
      license
      Not graded
      quality
      C
      maintenance
      Provides AI agents with zero-cost, zero-dependency trust evaluation for domains, URLs, wallets, APIs, and IPs, returning a 0-100 score with SSL, DNS, WHOIS, security header, and content sub-scores, plus batch comparison to rank multiple targets.
      MIT
    • A
      license
      A
      quality
      B
      maintenance
      Enables AI assistants to check whether a crypto token, link, or forwarded "gem" message is a scam by running contract rules, live test trades, creator history, and market data across 64 networks, returning plain-English or Pidgin verdicts. Also supports scanning messages, reviewing a token's past checks, and explaining individual findings.
      5
      MIT
    • F
      license
      Not graded
      quality
      D
      maintenance
      Provides real-time threat intelligence for AI agents, enabling checks on IPs, domains, URLs, hashes, CVEs, prompt-injection payloads, and malicious AI-skill/MCP-tool definitions against a free database of 890K+ IOCs.
      -
    • A
      license
      A
      quality
      A
      maintenance
      Enables AI agents to verify links and payments for scam risk before acting, returning deterministic allow/ask/deny verdicts with scores, reasons, and warnings using local checks.
      3
      1
      MIT

    TDQS

    A4.4/5.0

    Scored across 10 tools

    Disambiguation5/5

    Each tool has a distinct, non-overlapping purpose based on input type (phone, URL, email, text, document, QR) and operation mode (single vs. batch). The 'check_' prefix clearly identifies analysis tools, while 'batch_' and 'get_' group utility functions, leaving no ambiguity about which tool to invoke for a given scam verification task.

    Naming Consistency5/5

    All 10 tools follow a consistent snake_case verb_noun convention (check_phone, batch_url, get_status). The verb choices are semantically coherent: 'check' for analysis operations, 'batch' for bulk processing, and 'get' for administrative retrieval, creating a predictable naming scheme throughout the set.

    Tool Count5/5

    With 10 tools, the server hits the sweet spot for a scam verification API. The set includes single-item checks for six input types, batch variants for high-volume channels (phone/URL), and essential administrative tools (status/usage), with no redundant or filler tools.

    Completeness4/5

    The surface covers all major scam vectors (voice, web, email, SMS, physical documents, QR codes) with appropriate AI and database verification. Minor gap: batch operations are only available for phone and URL lookups, not for email, text, or document analysis, though this may reflect typical usage patterns.

    Maintenance

    ActivityInactive
    ResponsivenessUnresponsive