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actors-mcp-server

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by apify

Get dataset items

get-dataset-items
Read-onlyIdempotent

Retrieve output rows from an Apify dataset by dataset ID. Filter fields, set limit/offset, and skip empty items to access the exact results from an Actor run.

Instructions

Get items (rows) from a dataset — the output/results produced by an Actor run. Not metadata or schema — use get-dataset for counts and the field list, get-dataset-schema for a JSON schema from a sample. When the user provides a datasetId and asks to retrieve results, output, data, or rows, call this tool directly — do not call get-dataset first. Default limit is 20. Use clean=true to skip empty items and hidden fields.

USAGE:

  • Use when you need to read data from a dataset (all items or only selected fields).

USAGE EXAMPLES:

  • user_input: Retrieve results from dataset abc123

  • user_input: Get only metadata.url and title from dataset username~my-dataset

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
descNoIf true, results are returned in reverse order (newest to oldest).
omitNoComma-separated list of fields to exclude from results.
cleanNoIf true, returns only non-empty items and skips hidden fields (starting with #). Shortcut for skipHidden=true and skipEmpty=true.
limitNoMaximum number of items to return. Default is 20.
fieldsNoComma-separated list of fields to include in results. Fields in output are sorted as specified. Use dot notation for nested objects (e.g. "metadata.url"); the server auto-flattens parent prefixes.
offsetNoNumber of items to skip at the start. Default is 0.
flattenNoComma-separated list of fields to flatten (e.g. flatten="metadata" turns {"metadata":{"url":"x"}} into {"metadata.url":"x"}). Normally derived automatically from dot-notation in `fields`; specify only as a diagnostic override.
datasetIdYesDataset ID or username~dataset-name.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemsYesDataset items
limitYesLimit used for pagination
offsetYesOffset used for pagination
summaryYesSummary of the result
nextStepYesOne follow-up action with tool name
datasetIdYesDataset ID
itemCountYesNumber of items returned
totalItemCountYesTotal items in dataset
apifyConsoleUrlNoPersonalized Apify Console link to the dataset; present only for Console sessions
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds value by stating the default limit of 20, the effect of clean=true, and that this returns output/results. No contradictions.

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 well-structured with a purpose paragraph, a usage paragraph, and examples. It is concise enough (about 4 sentences plus examples) and front-loads the key verb and resource. Slightly verbose in the examples but generally efficient.

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?

Given 8 parameters, 100% schema coverage, output schema present, and clear annotations, the description provides sufficient context: behavioral defaults (limit, clean), usage distinctions, and field filtering guidance. It covers the essential aspects for agent invocation.

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

Parameters4/5

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

Schema description coverage is 100%, so baseline is 3. The description adds context beyond schema: 'Default limit is 20', 'Use clean=true to skip empty items and hidden fields', and clarifies the flatten parameter usage. This adds meaning for the agent.

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's purpose: 'Get items (rows) from a dataset — the output/results produced by an Actor run.' It distinguishes itself from related tools (get-dataset for metadata/schema, get-dataset-schema for JSON schema).

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

Usage Guidelines4/5

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

The description explicitly tells when to use this tool: 'When the user provides a datasetId and asks to retrieve results, output, data, or rows, call this tool directly — do not call get-dataset first.' It provides usage examples, but does not give explicit when-not conditions beyond the sibling distinction.

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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