Read-only phone intelligence for AI voice agents — line type, risk, DNC, signed receipts.
Return a labeled, low-confidence risk read for an inbound caller: a spam signal (0–100, higher = riskier), verstat passthrough, and a first-party do-not-contact (DNC) signal — without a name dip. A supplementary input to the agent's own policy, never a verdict on whether to accept or reject the call. Supply the call's STIR/SHAKEN verstat to fold it into the signal — a failed validation raises the risk.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | Phone number in E.164, e.g. +14155552671 (loose input is normalized). | |
| verstat | No | Optional STIR/SHAKEN verstat for THIS call — TN-Validation-Passed / -Failed / No-TN-Validation, or a full Identity / P-Asserted-Identity header value. When supplied it folds into the risk signal (a failed validation raises it). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint. Description adds behavioral context: 'low-confidence', impact of failed STIR/SHAKEN validation raising risk, and that it is never a final verdict. No contradiction.
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?
Description is a single concise paragraph that front-loads the primary output. Every sentence adds value with no redundancy. Could be slightly more structured with bullets, but efficient.
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 high schema coverage, no output schema, and low complexity, the description covers what is returned, how to use it, and its role. Missing explicit mention of return format but components are listed.
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?
Schema coverage is 100% with descriptions for both parameters. Description adds meaning: number is normalized, verstat can be full header, and that verstat folds into risk signal. Provides value beyond the schema.
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?
Specifically states it returns a risk read with spam signal, verstat passthrough, and DNC signal, and explicitly distinguishes from siblings by noting 'without a name dip' and as a 'supplementary input' not a verdict.
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?
Clearly indicates when to use (supplementary to agent's own policy, not a verdict) and mentions supplying verstat to influence risk. Lacks explicit when-not-to-use or alternative tool references, but context is strong.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Return a first-party do-not-contact signal (suppress / no_match / unknown) for a number, sourced ONLY from suppression preferences registered and verified by the number's own owner inside Numbers Online — never a copy of any government or licensed do-not-call registry. "suppress" = the owner asked not to be contacted on this channel; "no_match" = no suppression preference on record (absence of suppress is not consent); "unknown" = the number could not be evaluated. Comes with a signed receipt recording the status "as of T". Advisory input to the agent's own process — it does not assert that a call is lawful.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | Phone number in E.164, e.g. +14155552671 (loose input is normalized). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint, openWorldHint), description adds that the signal is sourced only from owner-registered preferences, never from government DNC registries, and comes with a signed receipt. No contradiction with 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?
Description is detailed but well-structured, explaining three outcomes, sourcing, and advisory nature. Slightly lengthy but efficient for the information conveyed.
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?
Given one parameter with full schema coverage, no output schema, and helpful annotations, the description fully covers the tool's purpose, return values, and limitations (not a legal assertion). Complete for its complexity.
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?
Schema coverage is 100% for the single parameter 'number', which is well described in the schema (E.164 with normalization). The description adds no extra meaning for the parameter beyond what the schema provides.
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?
Description clearly states it returns a do-not-contact signal (suppress/no_match/unknown) for a number, sourced only from the number's owner preferences, distinguishing it from government registries and sibling tools like caller_risk or phone_lookup.
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?
Description implies it is an advisory input and not a legal assertion, but lacks explicit guidance on when to use versus alternatives or when not to use. No exclusions mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Return only the deterministic fields for a number — validity, line type (mobile / fixed line / VoIP / …), range carrier, country, and formatting. No paid dip; a free, fast classification a voice agent can call before deciding to enrich.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | Phone number in E.164, e.g. +14155552671 (loose input is normalized). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, so the description adds useful context: it is free, deterministic (returns specific fields), and intended for pre-enrichment. No contradictions exist, and the description enhances understanding beyond 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 two concise sentences that front-load the core functionality. Every word is meaningful, with no redundancy or filler. The structure efficiently communicates purpose, output, and use case.
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?
Given the tool has one input, no output schema, and a simple operation, the description covers the returned fields and usage context. It lacks explicit details on return format or error handling, but the listed fields and deterministic nature provide sufficient completeness for a voice agent.
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 with a detailed description for the 'number' parameter. The tool description does not add new information about the parameter; it only restates the context. Therefore, the description provides no additional semantic value beyond the schema.
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 states the tool returns deterministic fields for a phone number, including validity, line type, carrier, country, and formatting. It explicitly distinguishes itself from paid enrichment tools by noting it is a free, fast classification a voice agent can call before enriching, which differentiates it from sibling tools like phone_lookup.
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 provides context by stating it is a 'free, fast classification a voice agent can call before deciding to enrich,' implying it should be used for preliminary checks. However, it does not explicitly mention when not to use it or name specific sibling alternatives, though the use case is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Return a supplementary, low-confidence intelligence bundle for a phone number: validity, formatting, line type, range carrier, country, caller name (CNAM, where available), STIR/SHAKEN verstat (supply the call's verstat to fold it into the spam signal), a labeled spam signal, and a first-party do-not-contact (DNC) signal — a suppression preference registered by the number's own owner, never a copy of any government registry. Advisory only — the agent keeps every routing and dialing decision.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | Phone number in E.164, e.g. +14155552671 (loose input is normalized). | |
| verstat | No | Optional STIR/SHAKEN verstat for THIS call — TN-Validation-Passed / -Failed / No-TN-Validation, or a full Identity / P-Asserted-Identity header value. When supplied it folds into the risk signal (a failed validation raises it). | |
| max_cache_age_seconds | No | Operator TTL control; 0 forces a fresh dip. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=true. The description adds valuable context: 'low-confidence', 'advisory only', and details that the DNC signal is first-party (not a government registry copy). No contradictions.
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 single long sentence with a list of returned fields, which is clear but could be more structured. It front-loads the purpose and is generally adequate without extra fluff.
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?
Despite no output schema, the description enumerates all return fields comprehensively. It covers the advisory nature and DNC specificity. Missing error or edge case handling, but overall complete for its intended use.
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?
Schema covers all 3 parameters (100% coverage). Description adds context for 'verstat' by explaining it folds into the spam signal. The other parameters are standard; the description doesn't repeat schema but adds slight extra value for the verstat parameter.
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 states it returns a 'supplementary, low-confidence intelligence bundle' for a phone number, listing specific data points (validity, formatting, line type, carrier, country, CNAM, STIR/SHAKEN, spam signal, DNC signal). It distinguishes from siblings by offering a combined bundle, while siblings like 'caller_risk', 'dnc_check', 'line_type' appear to focus on individual aspects.
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 says 'Advisory only — the agent keeps every routing and dialing decision', implying it's for intelligence, not actions. However, it does not explicitly guide when to use this tool vs siblings like 'caller_risk' or 'dnc_check'. Missing explicit when-to-use and when-not-to-use statements.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
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Phone carrier lookup, append, verification, DNC, and fraud data services.
Give AI agents a phone layer for consent-based calls, transcripts, summaries, and outcomes.
Give your AI agent a phone: place calls, navigate IVRs, wait on hold, get structured answers.
Give AI agents a phone: outbound AI calls that return a summary, transcript, and extracted fields.
Add one secure layer between your agents and this server.
Tools overlap significantly: phone_lookup includes spam signals and DNC check, while caller_risk and dnc_check provide more specific or constrained functionality. Descriptions help differentiate use cases, but an agent might struggle to choose between them.
All tool names use snake_case and are descriptive (e.g., caller_risk, dnc_check, line_type, phone_lookup). The pattern is mostly consistent, though verbs and noun combinations vary slightly.
Four tools cover the core needs of phone intelligence (quick classification, risk assessment, DNC check, comprehensive lookup) without redundancy. The scope is well-matched to the domain.
The set covers essential operations for phone intelligence: basic line info, risk, DNC, and a full lookup. Minor gaps exist (e.g., no tool for updating DNC preferences), but given the server's advisory role, these are acceptable.
