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Zabbix MCP Server

item_history_summary_get

Read-only

Retrieve item metadata, recent history, and min/max/avg statistics in one call to answer Zabbix trend and average questions without separate queries.

Instructions

Item metadata + last-N data points + min/max/avg statistics, in one call.

Use this for 'what was the average load on over the last hour?' / 'show me memory usage trend on '. Replaces the item_get + history_get + manual statistics loop the LLM has to write to answer trend questions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyNoItem key (used together with host).
hostNoHost name (used together with key).
limitNoMax history points to include (default 100).
itemidNoItem ID. Either itemid or (host + key) must be supplied.
periodNoTime window: '1h', '6h', '1d', '7d', '30d' (default '1h').1h
serverNoTarget Zabbix server. Available: default. Defaults to 'default' if omitted.
raw_jsonNoStrips the security disclaimer preamble from the response so it is pure JSON. Default: false. Requires the bearer token to have 'allow_raw_json' explicitly enabled by an operator in the admin portal - tokens without that policy receive a PolicyError instead. WARNING: setting true bypasses the prompt-injection mitigation marker that wraps untrusted Zabbix data (host names, item descriptions, problem text). LLM clients (Claude, GPT, Cursor, ...) should leave this false; only programmatic non-LLM consumers (Python scripts, n8n workflows that json.loads the result) should set true.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.41.0

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds that the call is a composite that avoids a manual loop, but discloses nothing about response wrapping, the security-disclaimer preamble, pagination, or how the time window interacts with the point limit — the notable behavioral detail (prompt-injection marker / raw_json policy) lives only in the schema, not here.

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?

Three tight sentences, front-loaded with the composite output, then usage examples, then the replacement rationale. No filler or restated field names.

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

Completeness4/5

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

An output schema exists, so return values need not be explained, and annotations carry the safety profile. Purpose and routing are complete; the only gap is that the response-wrapping/security-preamble behavior is left to the schema's raw_json description rather than surfaced in the tool description.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents all seven parameters including period formats, limit, the itemid vs host+key alternative, and the raw_json policy. The description adds no parameter-level meaning beyond that, so the baseline 3 applies.

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?

Names a concrete composite resource and its three outputs (metadata + last-N data points + min/max/avg stats), and explicitly distinguishes itself from the item_get/history_get pairing it replaces. An agent can tell at a glance this is the trend/summary tool, not a raw-fetch tool.

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 two concrete example questions that map to the tool's use case and names the alternatives it supersedes ('replaces the item_get + history_get + manual statistics loop'), giving clear routing guidance. It does not state explicit exclusions (e.g. 'use item_get alone if you only need metadata'), so it falls just short of a full when/when-not statement.

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