Callerapi

@callerapi check the reputation and carrier details for +14155552671

The number +14155552671 is a mobile line registered to T-Mobile USA in San Francisco, CA. Reputation score: 72/100 (moderate trust). No FTC complaints on record. Carrier type: wireless. This number has been flagged 3 times in spam databases but shows legitimate business activity. Last verified: 48 hours ago. Note: This is an illustrative example; actual reputation data varies by query time and database state.

This example demonstrates the MCP's core phone lookup capability. Requires the number in E.164 format (+country code). The reputation score aggregates multiple spam databases, but freshness depends on Callerapi's update cycle. Use this when validating inbound calls or screening contact lists.

@callerapi how many API credits do I have left this month?

Your Callerapi account (user@example.com) has 847 credits remaining out of a 1,000-credit monthly allocation. You've spent 153 credits so far this billing cycle, which resets on the 15th. Average daily usage: 5.1 credits. At current pace, you'll have ~600 credits left by month-end. This is an illustrative response; actual credit counts reflect real-time API usage.

This example shows account monitoring without leaving Switchy. Useful for teams managing shared API quotas. The MCP fetches live credit data, so you can gate expensive workflows (bulk lookups) based on remaining budget. No write access—this is read-only account introspection.

@callerapi look up these three numbers and tell me which ones are likely spam: +14155552671, +12125559876, +13105554321

Analyzed three numbers: +14155552671: Reputation 72/100, mobile/T-Mobile, 3 spam flags → Moderate risk. +12125559876: Reputation 28/100, landline/Verizon, 47 spam flags, 2 FTC complaints → High spam likelihood. +13105554321: Reputation 91/100, mobile/AT&T, 0 flags → Low risk, likely legitimate. Recommendation: Block or screen +12125559876. The other two appear safe for callback. This is an illustrative synthesis; actual risk scores depend on current database state.

This example pairs the MCP's lookup tool with AI reasoning to triage a list. Each lookup consumes 1 credit (3 total here), so batch requests burn quota quickly. The AI interprets reputation scores, but final spam decisions should factor your own call context and risk tolerance.

When Callerapi makes sense for pre-call vetting at scale

A 3-person sales team runs cold outreach campaigns and needs to scrub phone lists before dialing. Callerapi's reputation lookup catches known spam numbers and flags FTC complaints, which saves the team from burning credibility on bad contacts. The two-tool scope is narrow—you get number reputation and credit tracking, nothing else—so this works if your workflow is just "validate numbers, export clean list, hand off to dialer." If you need deeper enrichment (company size, technographics, email append), you'll stack another MCP on top. The API key auth is straightforward for a shared workspace. This MCP wins when your bottleneck is list quality and you're dialing 500+ numbers a month. Below that volume, manual spot-checks are faster than setting up the integration.

Using Callerapi to flag high-risk inbound calls

A 6-person support team at a fintech startup fields 200 inbound calls a week, and a handful are social engineering attempts. Callerapi's reputation tool surfaces carrier details and complaint history in real time, so the agent can escalate suspicious numbers to fraud ops before sharing account info. The limitation: you only get what's in the E.164 lookup—no call recording analysis, no sentiment scoring. If your fraud playbook needs more context (like cross-referencing the number against your CRM or checking recent ticket history), you'll need a second MCP for that lookup. This setup works when the fraud signal is in the number itself, not the conversation. For teams handling PII or payments, the reputation check is a cheap first gate. If fraud attempts are rare (under 5 a month), the manual lookup overhead isn't worth automating.

When Callerapi's credit tracking supports call documentation

A 4-person compliance team at a debt collection agency must log every outbound call attempt and prove due diligence on number validation. Callerapi's user info tool tracks credit usage per lookup, which maps to a per-call audit record when paired with your call log. The two-tool limit means you're not getting transcription or consent tracking here—just number validation and usage accounting. If your compliance framework requires richer metadata (call duration, recording storage, opt-out status), you'll need a separate MCP for those fields. This MCP fits when the regulatory ask is "prove you validated the number before calling" and your call volume justifies API credits over manual checks. For teams making under 100 regulated calls a month, a spreadsheet and manual lookups are simpler than managing API key rotation and credit budgets.