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Marc-Lou-Org

@datafast/mcp-server

by Marc-Lou-Org

Get Timeseries Data

get_timeseries

Fetch time series analytics data (visitors, sessions, revenue, conversion rate) with configurable intervals to uncover trends and support charting.

Instructions

Get time series analytics data with configurable intervals (hour, day, week, month). Returns visitors, sessions, revenue, and conversion rate over time. Great for trend analysis and charts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
osNoFilter by operating system
refNoFilter by ref parameter
viaNoFilter by via parameter
cityNoFilter by city
pageNoFilter by page path
endAtNoEnd date in ISO 8601 format (e.g. 2025-01-31T23:59:59Z)
limitNoNumber of results to return (1-1000, default: 100)
deviceNoFilter by device type (desktop, mobile, tablet)
fieldsYesComma-separated fields to include: visitors, sessions, revenue, conversion_rate
offsetNoNumber of results to skip (default: 0)
regionNoFilter by region
sourceNoFilter by source parameter
browserNoFilter by browser (e.g. Chrome, Safari)
countryNoFilter by country code (e.g. US, GB)
startAtNoStart date in ISO 8601 format (e.g. 2025-01-01T00:00:00Z)
hostnameNoFilter by hostname
intervalYesTime interval for data points
referrerNoFilter by referrer URL
timezoneNoIANA timezone (e.g. America/New_York). Defaults to website timezone
utm_termNoFilter by UTM term
entry_pageNoFilter by entry page path
utm_mediumNoFilter by UTM medium
utm_sourceNoFilter by UTM source
utm_contentNoFilter by UTM content
utm_campaignNoFilter by UTM campaign
Behavior3/5

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

With no annotations, the description must carry the behavioral disclosure. It does state the returned metrics and that data is over time with configurable intervals, which is helpful. However, it omits important behaviors such as default intervals, pagination, filtering behavior, and how time periods are aggregated. This leaves significant gaps for a complex tool, so a score of 3.

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 three sentences long, front-loaded with the action and outcome, and includes a brief use-case. Every sentence provides useful information; no unnecessary repetition. Score 5.

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?

Given the tool has 25 parameters and no output schema, the description is too brief to fully contextualize the tool's behavior. It doesn't explain the response format, grouping, pagination limits, or default timezone. While the schema covers parameters, the description doesn't guide an agent on how to construct a valid call or interpret results, so it is incomplete for this complexity. Score 2.

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?

The input schema provides descriptions for all 25 parameters (100% coverage), so the baseline is 3. The description adds minimal extra meaning—it lists the possible fields and intervals, which already appear in the schema. It does not clarify the impact of filters or parameter combinations, so no bonus beyond baseline.

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 fetches time series analytics data with configurable intervals and lists the returned metrics (visitors, sessions, revenue, conversion rate). It uses a specific verb and resource, though it does not explicitly differentiate from sibling analytics tools, earning a 4 rather than 5.

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 usage for trend analysis and charts ('Great for trend analysis and charts'), but does not provide explicit guidance on when to use this tool versus alternatives like get_overview or get_realtime. No exclusions or alternatives are mentioned, so a score of 3.

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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