phone_validatorValidate and get information about a phone number. Returns the carrier, line type, country, and whether the number is valid.
| Name | Required | Description | Default |
|---|---|---|---|
| phone | Yes | The phone number to validate (E.164 format recommended, e.g., +14155552671) |
| Name | Required | Description | Default |
|---|---|---|---|
| data | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Output schema / (root)Previous value: -nullNew value: +{
+ "$schema": "http://json-schema.org/draft-07/schema#",
+ "additionalProperties": false,
+ "properties": {
+ "data": {}
+ },
+ "required": [
+ "data"
+ ],
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and openWorldHint, so the safety profile is clear. The description adds meaningful details about the return content (carrier, line type, country, validity). It does not contradict annotations, but it also does not disclose caveats such as data availability by region, external lookup behavior, or potential variability, which would have been valuable context.
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 short sentences with no filler. It leads with the primary action, states the resource, and enumerates the useful output fields. Every sentence earns its place.
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 one required parameter, a fully documented input schema, an output schema, and read-only annotations, the description is largely sufficient. The only missing element is a brief note about when carrier/line type may not be available or how this differs from phone_finder for discovery use cases.
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 schema provides 100% parameter documentation with a regex pattern, a description, and an example format for the 'phone' parameter. The description does not add additional parameter-level meaning beyond what is already in the schema, so the baseline score of 3 applies.
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 validates a phone number and lists the specific information returned: carrier, line type, country, and validity. This is a clear verb+resource description. However, it does not explicitly distinguish itself from sibling tools like phone_finder or mpp_phone_validator, so it falls short of full sibling differentiation.
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 use case is implied: use this tool when you need to validate a phone number or retrieve metadata about it. However, there is no explicit guidance on when to choose this over alternatives such as phone_finder, nor any exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Several tools have overlapping purposes: email_enrichment and person_enrichment are nearly identical, and every mpp_* tool duplicates a non-MPP tool with only payment method differences. Domain-related tools like domain_search, email_count, and domain_status also blur boundaries, making selection error-prone.
Most tools follow a readable snake_case convention with clear actions like list_, create_, get, and finder/verifier/enrichment suffixes. However, ordering is inconsistent (companies_search vs domain_search, combined_enrichment vs email_finder) and a few vague names like location and autocomplete break the pattern.
38 tools is excessive for this server's scope, especially since 10 are MPP variants that simply duplicate existing functionality with a different payment model. The core feature set could be expressed in roughly half the tools without losing capability.
The toolset covers the core Tomba workflows well: email finding, verification, enrichment, domain/company search, phone lookup, and lead management. Minor gaps exist, such as no update/delete operations for leads and no detailed lead retrieval, but agents can work around these for most prospecting tasks.