Discover available analytics tables and their summary metadata. Call this before nevent_analytics_query, then use nevent_analytics_table_schema to learn valid field names for a selected table.
| 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, covering the safety profile. The description adds contextual workflow details but does not disclose additional behavioral traits like response format, pagination, or rate limits. It is adequate but not rich, consistent with the bar set by 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 sentences with no redundancy. The core purpose is front-loaded, and the workflow guidance is delivered in a compact, directive sentence. Every word 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 discovery tool, the description is complete: it states the purpose, provides the correct invocation order relative to two key sibling tools, and the annotation title reinforces the intent. Nothing needed to call it correctly is missing.
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, so the baseline is 4. The description naturally has no parameter details to provide, and the schema fully covers the (empty) parameter set. No compensation is needed.
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 ('Discover'), a clear resource ('available analytics tables and their summary metadata'), and distinguishes itself from siblings by explicitly naming the workflow sequence with nevent_analytics_query and nevent_analytics_table_schema. This makes it immediately clear what the tool does and how it differs from related 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 description provides explicit usage guidance: 'Call this before nevent_analytics_query, then use nevent_analytics_table_schema...' This tells the agent exactly when to use this tool and what to use as the next step, effectively routing to the correct sibling tools without ambiguity.
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.
