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google-analytics-mcp

Get Traffic Sources

get_traffic_sources

Retrieve traffic source metrics from Google Analytics 4 for a specified date range and property, with optional grouping by dimensions to analyze acquisition.

Instructions

Get traffic source metrics for a specific date range from Google Analytics 4.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
end_dateYesEnd date in YYYY-MM-DD format
dimensionsNoList of dimensions to group by (optional, defaults to ["source", "medium"])
start_dateYesStart date in YYYY-MM-DD format
property_idYesGoogle Analytics 4 property ID (numeric, e.g., "123456789")

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It doesn't state whether the operation is read-only, how it handles invalid date ranges, pagination limits, or authentication requirements. The description is a bare statement of intent without any operational details.

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 a single, front-loaded sentence with no redundant wording. It states the action, target, and scope efficiently. Every word earns its place, and it's easy to parse.

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

Completeness2/5

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

Despite the presence of an output schema, the description lacks essential behavioral context such as error handling, rate limits, or usage conditions. For a tool with 4 parameters and no annotations, it feels incomplete for an agent to know how to call it correctly in various situations.

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 parameters like property_id, start_date, end_date, and dimensions are already documented in the schema. The description adds no additional semantic meaning beyond what the schema provides, so a baseline of 3 is 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 clearly states the tool retrieves traffic source metrics from Google Analytics 4 for a date range. The verb 'get' and resource 'traffic source metrics' are specific, and it distinguishes from siblings like get_page_views and get_active_users, though it doesn't explicitly name them.

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 provides no guidance on when to use this tool versus alternatives. It doesn't mention scenarios like comparing traffic sources or conditions that would make run_report more appropriate. There's no explicit when-to-use or when-not-to-use information.

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