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Pirsch Analytics MCP Server

pirsch_utm

Fetch UTM statistics grouped by dimension (source, medium, campaign, content, or term) to analyze marketing campaign performance.

Instructions

Get UTM stats by dimension (source, medium, campaign, content, term)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
osNo
toNoYYYY-MM-DD
tzNo
tagNo
cityNo
fromNoYYYY-MM-DD
pathNoSupports Pirsch operators like ~contains, !not, and ^does-not-contain
sortNo
typeYes
eventNo
limitNo
scaleNo
startNoPast seconds for active view
filterNo
offsetNo
searchNoContains search on the primary field, e.g. page path for page endpoints
browserNo
channelNo
countryNo
keywordNoGoogle Search Console keyword filter for keyword page lookups
patternNo
to_timeNoHH:MM (same-day only)
hostnameNo
languageNo
platformNo
referrerNo
utm_termNo
directionNo
domain_idNo
exit_pathNo
from_timeNoHH:MM (same-day only)
entry_pathNo
event_nameNoAlias for event when callers use event_name instead of event
session_idNo
utm_mediumNo
utm_sourceNo
visitor_idNo
path_prefixNoMCP-local path prefix filter for page-style tools, e.g. /tutorials/
utm_contentNo
screen_classNo
utm_campaignNo
include_titleNo
referrer_nameNo
event_meta_keyNo
custom_metric_keyNo
custom_metric_typeNo
include_avg_time_on_pageNo
Behavior2/5

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

With no annotations provided, the description carries full burden but omits any behavioral details such as side effects, authorization needs, or rate limits. It does not contradict annotations however.

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 a single, efficient sentence that front-loads the core purpose with no redundant words. It earns its place, though brevity sacrifices useful details.

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

Completeness1/5

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

Given the tool's complexity (47 parameters, nested objects, no output schema, no annotations), the description is severely incomplete. It fails to explain filtering options, pagination, or output format, leaving the agent with minimal guidance.

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

Parameters2/5

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

Schema description coverage is only 21%, yet the description only adds meaning to the required 'type' parameter by listing its enum values. The many other parameters (47 total) are not explained in the description.

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?

The description clearly states the tool retrieves UTM statistics and lists the supported dimensions (source, medium, campaign, content, term). This distinguishes it from sibling tools like pirsch_pages or pirsch_referrers, which focus on different metrics.

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

Usage Guidelines3/5

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

The description implies the tool is for UTM data, but provides no explicit guidance on when to use it versus alternatives, nor any exclusions or prerequisites.

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

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