locationGet employees location count by country for a domain
| Name | Required | Description | Default |
|---|---|---|---|
| domain | Yes | The domain name (e.g., 'stripe.com') |
| 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 indicate readOnlyHint and openWorldHint, so the safety profile is covered. The description adds the summary nature of the result (count by country), but does not explain details such as whether counts are approximate, whether all employees are included, or how country assignment works. It adds modest value beyond 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 a single, front-loaded sentence with no filler. It conveys the essential operation, object, and scope efficiently.
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 simple one-parameter read-only tool with an output schema and annotations, the description is mostly complete. However, slight ambiguity around 'location count' (number of employees per country vs. number of locations per country) means a bit more context could improve clarity without bloating the description.
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 a clear description and pattern for 'domain'. The tool description merely repeats 'for a domain' and adds no additional semantic meaning. Baseline 3 is appropriate because the schema already documents the parameter fully.
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 states a specific verb and resource: 'Get employees location count by country for a domain.' It clearly identifies the operation and input domain, though it does not explicitly differentiate from sibling tools like email_count or domain_search.
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?
There is no guidance on when to use this tool versus alternatives, no exclusions, and no mention of prerequisites. The description simply states what it does without contextual placement among the many sibling tools.
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.