Call this FIRST when you need to build or target an audience. Returns all saved segments for the active tenant: id, name, estimated contact count, and last-execution date. Use the returned segment ids to call nevent_get_segment (for the filter definition), nevent_segment_preview (to verify the audience), or nevent_create_campaign (to send a campaign to that segment).
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context by specifying that results are scoped to the active tenant and by enumerating the returned fields, which is helpful given there is no output schema.
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?
Three tight sentences with no filler. The first sentence front-loads the primary call-to-action, the second states the return data, and the third provides follow-up tool routing. 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 zero-parameter, read-only list operation, the description is complete: it explains when to invoke it, what it returns, and what to do with the results. The absence of an output schema is mitigated by listing the returned fields explicitly.
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 tool has zero parameters and an empty input schema, so there is no parameter ambiguity to resolve. The description correctly avoids inventing parameters and instead focuses on the return contract, which is the only semantically relevant information.
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 action: returns all saved segments for the active tenant, and lists the exact fields returned (id, name, estimated contact count, last-execution date). It clearly distinguishes this tool from segment-related siblings by framing it as the entry point and naming downstream tools.
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 opening phrase 'Call this FIRST when you need to build or target an audience' explicitly prescribes when to use the tool. It also provides concrete routing guidance: use returned segment ids to call nevent_get_segment, nevent_segment_preview, or nevent_create_campaign, clarifying how it fits into the broader workflow.
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.
Most domain groups are distinct, but the campaign reporting cluster has three tools returning overlapping engagement metrics (get_campaign, get_campaign_metrics, campaign_report), and paid_ads_status vs paid_ads_health have fuzzy boundaries. The detailed descriptions mitigate but do not eliminate the risk of an agent calling the wrong tool.
All names use the nevent_ prefix and snake_case, and most CRUD operations follow verb_noun. However, several tools reverse the order or drop the verb entirely (segment_preview, segment_execute, campaign_report, paid_ads_status, analytics_query), making the convention mixed but still readable.
With 59 tools, this is far above the 25+ 'too many' threshold and falls into the 50+ extreme range. The broad domain coverage explains some of the size, but for an agent the set is likely to be overwhelming and harder to navigate than a more focused server.
The core marketing workflow (segments, templates, campaign creation, quote, schedule, metrics) is covered, but there is no way to update, cancel, or delete a campaign, and templates and segments lack delete operations. These are notable lifecycle gaps that agents will hit when users want to change or clean up resources.
