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Zabbix MCP Server

token_get

Read-only

Retrieve Zabbix API tokens to audit or list persistent credentials for scripts, integrations, and service accounts, with filters for user, status, and expiry.

Instructions

Retrieve API tokens. Tokens provide persistent authentication for scripts, integrations, and service accounts without requiring user.login sessions. Each token is bound to a specific user and inherits that user's permissions. Tokens have optional expiry dates and can be enabled or disabled independently.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of results to return.
filterNoReturn only results whose properties exactly match the given values (a single value or a list of values per key). Example: {"status": 0} or {"status": [0, 1]}. Keys: created_at, creator_userid, expires_at, lastaccess, name, status, tokenid, userid. Text properties cannot be filtered; use 'search' for them.
outputNoProperties of the token object to return. Pass 'extend' for all, 'count' for the number of matches only, or a comma-separated list of property names. Default when omitted: tokenid, name, userid, status, expires_at. Properties: created_at, creator_userid, description, expires_at, lastaccess, name, status, tokenid, userid.
searchNoReturn results whose string properties contain the given pattern (case-insensitive; '*' is a wildcard when searchWildcardsEnabled is true). Example: {"name": "web"}. Keys: description, name.
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.
tokenidsNoReturn only tokens with the given IDs.
sortfieldNoSort by one or more of: tokenid, name, lastaccess, status, expires_at, created_at (comma-separated for several; pair with 'sortorder'). No other property is sortable.
sortorderNoSort order: 'ASC' (ascending) or 'DESC' (descending).
countOutputNoReturn the count of matching results instead of the actual data.
searchByAnyNoIf true, return results matching ANY search field (OR). Default is ALL fields (AND).
extra_paramsNoOther native token.get parameters, merged into the request as-is. Parameters: expired_at, token, userids, valid_at. Any other key is refused here, because Zabbix would silently ignore it. For a parameter you are sure exists on your release but is not listed, use zabbix_raw_api_call.
searchWildcardsEnabledNoIf true, enable * and ? wildcards in search patterns.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.41.0

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, covering the safety profile. The description adds useful token-domain context (persistent auth, user binding, permission inheritance, optional expiry, enabled/disabled state) but does not disclose tool-specific behavior such as auth requirements, rate limits, or pagination.

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

Conciseness4/5

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

The description is front-loaded with its purpose and consists of four concise, well-structured sentences. The token-model context is helpful but slightly more expansive than strictly necessary for invoking the tool.

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?

With 13 fully documented optional parameters, a rich output schema, and annotations covering the read-only safety profile, the description only needs to establish purpose and context. It does so adequately, though it omits explicit usage guidance that would make the definition fully self-contained.

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 13 parameters in detail. The description adds no parameter-specific meaning beyond what the schema provides, making the baseline score of 3 appropriate.

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

Purpose4/5

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

The description states a clear verb and resource: 'Retrieve API tokens.' It distinguishes the resource from other _get siblings such as user_get or host_get, but does not explicitly contrast itself with any similar tool, so it falls just short of the top score.

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

Usage Guidelines2/5

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

The description explains what tokens are but gives no guidance on when to call token_get versus alternatives. There are no exclusions, prerequisites, or selection criteria for the tool itself.

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