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Simple Analytics MCP by usefulapi

by io.usefulapi
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Export raw data points

simpleanalytics_export_datapoints
Read-only

Raw, unsampled page views or events of one website for a date range, as rows with only the fields asked for. The reply is capped at max_rows (default 100, max 1000) rows and 2 MB; "truncated" says more exist, so narrow the range. Rows are cut to about 40 000 characters of JSON. Dates: YYYY-MM-DD, or YYYY-MM-DDTHH for one hour (start and end the same day). Robots are left out unless asked. Needs the user id too. Export API: GET /api/export/datapoints.

Input Schema

NameRequiredDescriptionDefault
endYesEnd date, inclusive.
typeNoPage views (default) or events.
startYesStart date (see description).
fieldsNoFields to export (default added_iso, path, country_code, device_type, document_referrer). All: added_date, added_iso, added_unix, browser_name, browser_version, country_code, datapoint, device_type, document_referrer, duration_seconds, hostname, hostname_original, is_robot, is_unique, lang_language, lang_region, os_name, os_version, path, path_and_query, query, referrer_hostname, referrer_path, screen_height, screen_width, scrolled_percentage, session_id, user_agent, utm_campaign, utm_content, utm_medium, utm_source, utm_term, uuid, viewport_height, viewport_width, metadata.<key>_<text|int|bool|date>. datapoint is for events only; duration_seconds, is_unique and scrolled_percentage for pageviews only.
hostnameYesWebsite hostname as shown in Simple Analytics, e.g. example.com (from simpleanalytics_list_websites).
max_rowsNoMaximum rows returned (default 100).
timezoneNoIANA time zone, e.g. Europe/Amsterdam. Default: the website setting.
include_robotsNoInclude robot/crawler traffic (default false).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior5/5

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

Annotations only declare readOnlyHint=true, yet the description adds substantial behavioral context: a rows/2 MB cap, a 'truncated' flag signaling more data, a ~40k character JSON row limit, default robot exclusion, and a user-id requirement. This is exactly the beyond-annotation disclosure the tool needs.

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?

Front-loaded with the core purpose, then dense but purposeful sentences on caps, date formats, and defaults. Every clause carries information, though the run of limit details is slightly packed.

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?

For a read-only export with no output schema, the description covers truncation behavior, size limits, date formats, and defaults well. It stops short of characterizing the row/field output shape, but the 'truncated' and field-set mentions give the agent enough to call it correctly.

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 coverage is 100%, so the schema already documents all 8 parameters and the baseline is 3. The description reinforces date syntax and the max_rows cap and notes the default field set, but largely restates schema content rather than adding new semantics.

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?

States a specific verb and resource: 'Raw, unsampled page views or events of one website for a date range.' The word 'raw' vs. the aggregate-oriented siblings (stats, timeseries, breakdown) implicitly positions it, but no sibling is named to make the distinction explicit.

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?

Offers operational guidance ('narrow the range' when truncated, hour-granularity rules), which is implied usage context. However, it never states when to choose this over simpleanalytics_get_stats or get_events, so the agent must infer the raw-export role.

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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