zscaler-mcp-server

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by zscaler

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Python

Hybrid

zins_get_cyber_incidents_daily

Read-only

Get the daily cyber-security incident trend over time. Read-only analytics.

Instructions

Get the daily cyber-security incident trend over time. Read-only analytics.

Groups incidents by day (categorize_by=TIME) so you can spot spikes across the window. Window must be a 7- or 14-day historical interval.

Input Schema

TableJSON Schema

Name	Required	Description
`limit`	No
`query`	No	Optional JMESPath expression applied to the results after the API call, for client-side filtering and projection. Examples: "[?enabled==`true`]", "[*].{name: name, id: id}", "length(@)". Omit to get the full records. IMPORTANT: field names are the keys of the returned records, which are usually snake_case (`custom_category`) even where the Zscaler API documents camelCase (`customCategory`) — guessing the spelling yields an empty list that looks like a real answer. If you have not already seen a record from this tool, call it once without `query` and read the keys off the response.
`end_time`	No
`start_time`	No
`end_days_ago`	No
`start_days_ago`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed9 schema fields changedv0.15.3Aug 19, 2026

removedInput schema / additionalProperties
```
Removed value: -false
```
addedInput schema / properties / end_days_ago / title
```
Added value: +"End Days Ago"
```
addedInput schema / properties / end_time / title
```
Added value: +"End Time"
```
addedInput schema / properties / limit / title
```
Added value: +"Limit"
```

changedInput schema / properties / query / description

Previous value: -"Optional JMESPath expression applied to the results after the API call, for client-side filtering and projection. Field names are exactly what the Zscaler API returns. Examples: \"[?enabled==`true`]\", \"[*].{name: name, id: id}\", \"length(@)\". Omit to get the full records."New value: +"Optional JMESPath expression applied to the results after the API call, for client-side filtering and projection. Examples: \"[?enabled==`true`]\", \"[*].{name: name, id: id}\", \"length(@)\". Omit to get the full records. IMPORTANT: field names are the keys of the returned records, which are usually snake_case (`custom_category`) even where the Zscaler API documents camelCase (`customCategory`) — guessing the spelling yields an empty list that looks like a real answer. If you have not already seen a record from this tool, call it once without `query` and read the keys off the response."

addedInput schema / properties / query / title
```
Added value: +"Query"
```
addedInput schema / properties / start_days_ago / title
```
Added value: +"Start Days Ago"
```
addedInput schema / properties / start_time / title
```
Added value: +"Start Time"
```

addedInput schema / title

Added value: +"zins_get_cyber_incidents_dailyArguments"

Changed14 schema fields changedv0.14.0Jul 28, 2026

addedInput schema / additionalProperties
```
Added value: +false
```

removedInput schema / properties / end_days_ago / description

Removed value: -"Days ago for end. Default: 2. Interval = start - end must be 7 or 14."

removedInput schema / properties / end_days_ago / title
```
Removed value: -"End Days Ago"
```

removedInput schema / properties / end_time / description

Removed value: -"ALTERNATIVE: End time as Unix epoch in MILLISECONDS."

removedInput schema / properties / end_time / title
```
Removed value: -"End Time"
```

removedInput schema / properties / limit / description

Removed value: -"Maximum number of daily entries to return (1-1000)."

removedInput schema / properties / limit / title
```
Removed value: -"Limit"
```

addedInput schema / properties / query

Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "Optional JMESPath expression applied to the results after the API call, for client-side filtering and projection. Field names are exactly what the Zscaler API returns. Examples: \"[?enabled==`true`]\", \"[*].{name: name, id: id}\", \"length(@)\". Omit to get the full records."
+}

removedInput schema / properties / start_days_ago / description

Removed value: -"Days ago for start. Default: 16 (14-day interval). API requires intervals of exactly 7 or 14 days."

removedInput schema / properties / start_days_ago / title
```
Removed value: -"Start Days Ago"
```

removedInput schema / properties / start_time / description

Removed value: -"ALTERNATIVE: Start time as Unix epoch in MILLISECONDS."

removedInput schema / properties / start_time / title
```
Removed value: -"Start Time"
```

removedInput schema / title

Removed value: -"zins_get_cyber_incidents_dailyArguments"

changedOutput schema / (root)

Previous value: -{
-  "properties": {
-    "result": {
-      "items": {
-        "additionalProperties": true,
-        "type": "object"
-      },
-      "title": "Result",
-      "type": "array"
-    }
-  },
-  "required": [
-    "result"
-  ],
-  "title": "zins_get_cyber_incidents_dailyOutput",
-  "type": "object"
-}New value: +null

First observedv0.12.7Jun 24, 2026

TDQS

A3.8/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Discloses that it is read-only analytics and mentions grouping by day (categorize_by=TIME). This goes beyond the readOnly annotation by explaining the grouping behavior, but still lacks details on potential failures or edge cases.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two short, focused paragraphs with no filler. Every sentence conveys essential information about the tool's function and constraints.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers the purpose and a key constraint (window length) but lacks explanation of parameter semantics and output structure. Since no output schema is provided, the description could be more complete about what the trend data looks like.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Only the 'query' parameter has a description (from the schema). The description does not explain how to specify the time window using start_time, end_time, start_days_ago, or end_days_ago, leaving most parameters completely undocumented.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states the tool retrieves daily cyber-security incident trends over time, and distinguishes from siblings by specifying 'daily' and 'over time'. The read-only analytics note reinforces its purpose.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides a specific usage constraint: the window must be 7- or 14-day historical interval. This implies when to use (for spotting spikes) but does not explicitly contrast with alternatives like by-location or by-threat variants.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server

zins_get_cyber_incidents_daily

Instructions

Input Schema

Schema Changelog

TDQS

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