Ip2Location

@Ip2Location check the geolocation for these IPs from our server logs: 8.8.8.8, 1.1.1.1, and 104.16.132.229

Here's the geolocation data for those three IPs: • 8.8.8.8: Mountain View, California, US (37.4056, -122.0775) — ISP: Google LLC • 1.1.1.1: Sydney, New South Wales, AU (-33.8591, 151.2002) — ISP: Cloudflare • 104.16.132.229: San Francisco, California, US (37.7621, -122.3971) — ISP: Cloudflare All three are major infrastructure providers. The bulk lookup processed these in a single API call, consuming 3 credits from your account balance.

Bulk IP Geolocation is the fastest way to process multiple addresses — up to 1000 IPs per request. Each IP consumes one API credit. Accuracy varies by IP type: datacenter IPs return city-level precision, while residential IPs may be less granular depending on the database subscription tier.

@Ip2Location is 185.220.101.34 coming through a VPN or proxy? We're seeing suspicious login attempts from this address.

Yes, 185.220.101.34 is flagged as a TOR exit node. IP2Proxy detection shows: • Proxy Type: TOR • Country: Germany • Threat Level: High • ISP: Hetzner Online GmbH This IP is part of the TOR anonymization network, commonly used to mask true origin. The threat classification reflects elevated risk for fraud or abuse scenarios. Consider blocking or requiring additional authentication steps for requests from this address.

IP2Proxy detection identifies anonymizing services (VPNs, proxies, TOR) that mask a user's true location. This is critical for fraud prevention, but note that legitimate privacy-conscious users also rely on these tools. Each proxy check consumes one API credit. Results depend on your IP2Proxy database subscription level.

@Ip2Location calculate the distance between our CDN edge at 13.107.42.14 and the user IP 203.0.113.45, then summarize whether we should route through a closer node.

The distance between these IPs is approximately 12,847 km (7,982 miles): • 13.107.42.14: Redmond, Washington, US (Microsoft Azure) • 203.0.113.45: Sydney, New South Wales, AU Given this 12,800+ km separation, routing through a closer edge node would significantly reduce latency. If you have a Sydney or Singapore presence, that would cut the distance by ~80%. The current path likely adds 150-200ms round-trip time compared to a regional node.

Distance calculation uses straight-line geographic distance between geolocated IPs — useful for CDN routing decisions and latency estimation. The AI can interpret this data in context (like suggesting closer nodes), but actual network latency depends on peering, routing policies, and congestion. Each distance calculation consumes two API credits (one per IP).

When IP2Location catches proxy abuse before payment

A 6-person e-commerce team sees chargebacks cluster around VPN traffic. They wire IP2Proxy into their checkout flow to flag anonymizing IPs before the payment gateway runs. The proxy detection tool returns a risk score in under 200ms, fast enough to block suspicious orders without adding friction for real customers. The bulk geolocation tool handles batch analysis of historical orders to map fraud patterns by region. This works when your fraud volume justifies the API cost—if you're processing under 500 transactions a day, the credit burn might outpace the chargeback savings. For teams running Stripe or Shopify with a fraud problem, this MCP turns IP intelligence into a pre-authorization gate.

When geolocation steers users to the right regional experience

A 3-person SaaS startup serves customers across EMEA and APAC with different pricing tiers and compliance rules per region. They use the IP geolocation tool to route new signups to the correct regional instance and pre-fill country selectors in onboarding forms. The distance calculator helps their support team verify latency complaints by measuring geographic separation between a user's IP and the nearest data center. This setup assumes your user base is large enough to justify the API overhead—if you're under 1,000 monthly signups, a simpler GeoIP library might be cheaper. For teams with regional infrastructure and compliance boundaries, this MCP automates the routing logic that used to require manual user input.

When WHOIS lookups speed up abuse response

A 5-person DevOps team monitors login attempts from unfamiliar IPs and needs to decide which ones warrant blocking. They use the domain WHOIS lookup to identify the registrant behind suspicious traffic sources, and the hosted domains tool to see if an IP is running known phishing infrastructure. The bulk geolocation tool processes server logs in batches to map attack origins during post-incident reviews. This works when your security posture requires human-in-the-loop decisions—if you're automating blocks at scale, a dedicated threat intel feed is faster. For teams triaging abuse reports or investigating account takeovers, this MCP turns raw IPs into actionable context without leaving the terminal.