Skip to main content
Glama

New Shopify Stores Radar

Server Details

New and pre-launch Shopify stores from public CT logs: RDAP date, niche, country. No PII.

Ownership verified
Status
Healthy
Uptime
98.9% over 21 days
Last Tested
Transport
Streamable HTTP · MCP 2025-11-25
URL
Repository
yzf75011-ui/prelaunch-radar-mcp
GitHub Stars
0
Server Listing
new-shopify-stores

TDQS

A4.1/5.0

Scored across 5 tools

Disambiguation4/5

The four generic Apify tools (abort run, get run, get dataset items, get KV record) target clearly distinct resources and actions. The only mild overlap is that the prelaunch-radar tool both runs an Actor and returns its results, which partially overlaps with get-dataset-items, but the boundary is understandable.

Naming Consistency4/5

Four tools follow a clean kebab-case verb_noun pattern (abort-actor-run, get-actor-run, get-dataset-items, get-key-value-store-record). The fifth tool is an auto-generated, doubled-hyphen actor slug that breaks the pattern badly, though it is a single outlier.

Tool Count4/5

Five tools is a reasonable, well-scoped set for running a single Actor and consuming its output. It is slightly thin on domain-specific functionality, since only one tool actually concerns the Shopify store radar itself.

Completeness4/5

The surface covers the run lifecycle well: start the actor (prelaunch tool), poll status, fetch dataset rows, read KV records, and abort. Minor gaps exist (no generic run-actor tool, no listing/pagination across runs or datasets), but the core workflow is covered.

Available Tools

5 tools
abort-actor-runAbort Actor runA
DestructiveIdempotent
Inspect

Abort an Actor run that is currently starting or running. For runs with status SUCCEEDED, FAILED, ABORTING, ABORTED, or TIMED-OUT, this call has no effect. The results will include the updated run details after the abort request.

USAGE:

  • Use when you need to stop a run that is taking too long or misconfigured.

USAGE EXAMPLES:

  • user_input: Abort run y2h7sK3Wc

  • user_input: Gracefully abort run y2h7sK3Wc

ParametersJSON Schema
NameRequiredDescriptionDefault
runIdYesThe ID of the Actor run to abort.
gracefullyNoIf true, the Actor run will abort gracefully with a 30-second timeout.

Output Schema

ParametersJSON Schema
NameRequiredDescription
tipNoAdvisory guidance RAG Web Browser wrote to its key-value store under the reserved "TIP" key
runIdYesActor run ID
statsNoRun statistics
statusYesRun status: READY | RUNNING | TIMING-OUT | TIMED-OUT | ABORTING | ABORTED | SUCCEEDED | FAILED
actorIdYesStable Apify Actor ID from the run record
summaryYesPast-tense summary of the run state
exitCodeNoActor process exit code; populated for terminal states (especially FAILED)
nextStepYesOne primary follow-up action with identifiers interpolated
storagesYesDataset and key-value store metadata, keyed by alias. "default" is always the primary entry.
actorNameNo"username/actor-name"
startedAtNoISO timestamp when the run started
finishedAtNoISO timestamp when the run finished (terminal states only)
statusMessageNoPass-through from Apify run.statusMessage
apifyConsoleUrlNoPersonalized Apify Console link to the run; present only for Console sessions

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare destructiveHint=true, idempotentHint=true, readOnlyHint=false, so the safety profile is covered. The description adds real behavioral context beyond that: the no-effect-on-terminal-states rule, which is exactly what makes the idempotent hint meaningful, plus the fact that updated run details come back. It omits auth/permission requirements and any rate-limit behavior.

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 action and the state constraint, and every prose sentence earns its place. The 'USAGE EXAMPLES' block of raw user_input lines is mostly decorative and pads the definition slightly.

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?

With an output schema present, return values need not be spelled out, and the description still notes that updated run details are returned. For a two-parameter mutation with full annotation coverage, only auth requirements are unaddressed, which is a minor gap.

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 both parameters and the 30-second graceful-abort timeout are already documented in the schema. The description only gestures at 'gracefully' via an example, adding no syntax or semantic meaning beyond the schema. Baseline 3 applies.

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?

Specific verb (Abort) plus resource (Actor run) and a state qualifier ('currently starting or running'), which immediately distinguishes it from siblings like call-actor and get-actor-run. An agent can select it without opening the 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?

Explicit when-to-use ('stop a run that is taking too long or misconfigured') and an explicit no-op condition (terminal statuses such as SUCCEEDED, FAILED, ABORTED, TIMED-OUT). It does not name an alternative tool or describe prerequisites, so it falls short of a 5.

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

get-actor-runGet Actor runA
Read-onlyIdempotent
Inspect

Get detailed information about a specific Actor run.

Returns run result: status, storages (datasets/keyValueStores alias map), stats, summary, nextStep.

  • summary describes the past (e.g. "SUCCEEDED in 22s. 47 items; 3 fields available.").

  • nextStep prescribes one primary follow-up action with identifiers interpolated (e.g. "Use get-dataset-items with datasetId=...").

  • waitSecs (0–45, default 30) waits up to that many seconds for terminal status before returning.

USAGE:

  • Use to check the status of a run started by any Actor-running tool.

  • Pass waitSecs > 0 to block until terminal (or until the cap elapses).

USAGE EXAMPLES:

  • user_input: Show details of run y2h7sK3Wc

  • user_input: Wait for run y2h7sK3Wc to finish

ParametersJSON Schema
NameRequiredDescriptionDefault
runIdYesThe ID of the Actor run.
waitSecsNoMaximum seconds to wait for the run to reach a terminal state (SUCCEEDED, FAILED, ABORTED, TIMED-OUT). 0 returns immediately with the current status. Cap: 45. Default: 30.

Output Schema

ParametersJSON Schema
NameRequiredDescription
tipNoAdvisory guidance RAG Web Browser wrote to its key-value store under the reserved "TIP" key
runIdYesActor run ID
statsNoRun statistics
statusYesRun status: READY | RUNNING | TIMING-OUT | TIMED-OUT | ABORTING | ABORTED | SUCCEEDED | FAILED
actorIdYesStable Apify Actor ID from the run record
summaryYesPast-tense summary of the run state
exitCodeNoActor process exit code; populated for terminal states (especially FAILED)
nextStepYesOne primary follow-up action with identifiers interpolated
storagesYesDataset and key-value store metadata, keyed by alias. "default" is always the primary entry.
actorNameNo"username/actor-name"
startedAtNoISO timestamp when the run started
finishedAtNoISO timestamp when the run finished (terminal states only)
statusMessageNoPass-through from Apify run.statusMessage
apifyConsoleUrlNoPersonalized Apify Console link to the run; present only for Console sessions

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive, but the description adds real behavioral context beyond them: the summary vs. nextStep semantics, and that waitSecs blocks for up to 45s (default 30) before returning the current state. This is substantive added value, though it doesn't cover error/failure modes.

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 segmented into Returns/USAGE/EXAMPLES blocks. Every line carries information, though the two usage examples are somewhat redundant with the USAGE prose, adding minor length.

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

Completeness5/5

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

With an output schema present and 100% parameter coverage, the description need only orient the agent, which it does fully: purpose, when to use, wait semantics, and concrete invocation examples. Nothing needed to call it correctly is missing.

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 coverage is 100%, so the baseline is 3, but the description goes further by framing waitSecs as a blocking/wait mechanism with its cap and default, and by describing what runId's run produces. Slight above-baseline value over the schema text.

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 ('Get detailed information about a specific Actor run') and enumerates the returned result fields (status, storages, stats, summary, nextStep). It does not explicitly distinguish itself from siblings like call-actor or abort-actor-run, so it falls just short of the 5 benchmark.

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 USAGE block names the condition ('check the status of a run started by any Actor-running tool') and explains when to pass waitSecs > 0 to block until terminal. It gives clear context but stops short of explicit exclusions or naming the sibling to use for other run operations.

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

get-dataset-itemsGet dataset itemsA
Read-onlyIdempotent
Inspect

Get items (rows) from a dataset — the output/results produced by an Actor run. Returns the rows themselves, not dataset metadata, counts, or a schema. When the user provides a datasetId and asks to retrieve results, output, data, or rows, call this tool directly. 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

ParametersJSON 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

ParametersJSON Schema
NameRequiredDescription
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

TDQS

A4.3/5.0
Behavior4/5

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

With annotations already declaring readOnlyHint=true and idempotentHint=true, the description adds valuable behavioral context: returns rows themselves, default limit of 20, and clean=true behavior. It also clarifies the nature of the return value beyond the schema.

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?

Well-structured with clear USAGE and USAGE EXAMPLES sections. Some redundancy ('Get items (rows)...' and 'Returns the rows themselves...') but overall efficient and front-loaded with purpose.

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 the tool has 8 parameters, an output schema, and rich annotations, the description adequately covers key behaviors, usage triggers, and examples. It doesn't explain every parameter but relies on the schema for that, which is appropriate.

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 coverage is 100%, so baseline is 3. The description adds extra meaning by explaining default limit (20) and the clean=true shortcut, which supplements the schema. It also provides examples for fields usage, though most parameter semantics are in the schema.

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?

Description clearly states the tool gets items (rows) from a dataset and explicitly distinguishes it from metadata, counts, or schema. It names the exact resource (dataset items) and the action (get), and provides direct trigger phrases for when to use it.

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?

Provides explicit use cases ('when the user provides a datasetId and asks to retrieve results...'), and clarifies what it is not for (metadata, counts, schema). However, it does not name alternative tools explicitly, only implies them.

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

get-key-value-store-recordGet key-value store recordA
Read-onlyIdempotent
Inspect

Get the value stored under a specific key in a key-value store — a single record, not a listing of all keys. Requires the exact key name. The response preserves the original Content-Encoding; most clients handle decompression automatically.

USAGE:

  • Use when you need to retrieve a specific record (JSON, text, or binary) from a store.

USAGE EXAMPLES:

  • user_input: Get record INPUT from store abc123

  • user_input: Get record data.json from store username~my-store

ParametersJSON Schema
NameRequiredDescriptionDefault
recordKeyYesKey of the record to retrieve.
keyValueStoreIdYesKey-value store ID or username~store-name.

Output Schema

ParametersJSON Schema
NameRequiredDescription
keyYesRecord key
valueYesThe stored value (JSON, text, or binary)
summaryYesSummary of the result
contentTypeNoMIME type of the stored value
keyValueStoreIdYesKey-value store ID

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive, closed-world behavior. The description adds genuine context beyond that: the exact key name is required, and the response preserves the original Content-Encoding with most clients decompressing automatically. That encoding note is real operational value an agent would otherwise not know.

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 action and scope, then a short behavioral note, then usage. The USAGE line slightly overlaps the first sentence, but the examples earn their space by showing realistic inputs. No filler.

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

Completeness5/5

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

With an output schema present there is no need to describe return values, and the annotations carry the safety profile. For a two-parameter read tool, the description supplies everything else an agent needs: exactness of the key, allowed value types, and the encoding caveat.

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 the baseline is 3. The description still adds a semantic constraint the schema omits — that the key must be an exact match — and the examples show the 'username~my-store' form of the store ID, gently reinforcing the ID format.

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?

Specific verb (get) + resource (value under a key in a key-value store) with an explicit scope boundary: 'a single record, not a listing of all keys.' None of the sibling tools overlap with this resource, and the anti-scope clause removes any ambiguity about whether it enumerates keys.

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 USAGE line gives a clear triggering condition — retrieving a specific record (JSON, text, or binary) — and two concrete examples anchor it. It lacks explicit when-not-to-use guidance or named alternatives, but no similar sibling exists to route against.

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

prelaunch-radar--new-shopify-stores-pre-launch-radarprelaunch-radar/new-shopify-stores-pre-launch-radar
Destructive
Inspect

This tool calls the Actor "prelaunch-radar/new-shopify-stores-pre-launch-radar" and retrieves its output results. Actor description: New Shopify stores, including pre-launch stores behind a password page, detected from public Certificate Transparency logs, with RDAP registration date, niche, country and catalog counts. Also checks any domain for Shopify. Flat JSON for AI agents and MCP. Zero personal data.

ParametersJSON Schema
NameRequiredDescriptionDefault
modeNofeed = list newly detected Shopify stores. enrich = check your own list of domains (fill 'domains'). Example values: "feed"feed
cursorNofeed mode only. Leave empty to use 'Detected in the last N days'. Put 'latest' once to get the current position without being charged, or 0 to start from the oldest store in the 30-day feed. Each run returns nextCursor in the OUTPUT record (and a 'cursor' field on every item): pass it to the next run to receive only stores added since, never the same store twice. Filters apply before billing. Stores excluded by your filters are skipped for good.
nichesNofeed mode only. Keep only these niches. Empty = all niches.
statusNofeed mode only. 'pre-launch' = store still behind its password page; 'live' = open storefront. Example values: "any"any
domainsNoenrich mode only. Domains or URLs, one per item, e.g. example.com. Up to maxItems are checked.
maxItemsNoHard cap on the number of billed results (stores or domains) for this run. Example values: 100
waitSecsNoMax seconds (0–45, default 30) to cap the wait for the Actor run to reach terminal state. For long-running Actors the response returns at the cap with the current run status; follow `nextStep` to poll via get-actor-run. Set to 0 to fire-and-forget.
countriesNofeed mode only. ISO 3166-1 alpha-2 codes of the store's country, e.g. US, GB, FR. Empty = all countries.
sinceDaysNofeed mode only, used when 'cursor' is empty. Return stores first detected in the last N days (1 = yesterday and today). Overlapping windows return (and bill) the same stores again: use 'cursor' for scheduled runs. Example values: 7
maxFeedAgeHoursNofeed mode with a cursor only. If the collector has not refreshed the feed for this long, the run fails without delivering or charging anything, and your cursor stays valid. Example values: 26
maxCheckAgeHoursNofeed mode only, optional. Keep only stores whose live / pre-launch status was re-checked in the last N hours (see 'status_checked_at'). Empty = no freshness filter.

Output Schema

ParametersJSON Schema
NameRequiredDescription
tipNoAdvisory guidance RAG Web Browser wrote to its key-value store under the reserved "TIP" key
runIdYesActor run ID
statsNoRun statistics
statusYesRun status: READY | RUNNING | TIMING-OUT | TIMED-OUT | ABORTING | ABORTED | SUCCEEDED | FAILED
actorIdYesStable Apify Actor ID from the run record
summaryYesPast-tense summary of the run state
exitCodeNoActor process exit code; populated for terminal states (especially FAILED)
nextStepYesOne primary follow-up action with identifiers interpolated
storagesYesDataset and key-value store metadata, keyed by alias. "default" is always the primary entry.
actorNameNo"username/actor-name"
startedAtNoISO timestamp when the run started
finishedAtNoISO timestamp when the run finished (terminal states only)
statusMessageNoPass-through from Apify run.statusMessage
apifyConsoleUrlNoPersonalized Apify Console link to the run; present only for Console sessions

Related MCP Connectors

Related MCP Servers

  • F
    license
    Not graded
    quality
    D
    maintenance
    DTC competitor intelligence: catalog snapshots, price history, cross-brand product comparison, and drop/restock detection for 84 Shopify-powered brands. Pay-per-call via Apify.
    -
  • A
    license
    A
    quality
    D
    maintenance
    Domain intelligence for DNS, WHOIS/RDAP, SSL/TLS, subdomain discovery, availability, valuation, email security, and typosquatting and brand protection.
    1
    1
    MIT
  • A
    license
    Not graded
    quality
    B
    maintenance
    Enables AI agents to read live Shopify catalog snapshots, detect product, price, and stock changes against stored baselines, and produce competitor intelligence reports across single stores or batches of up to 50. Paid tiers settle automatically in USDC on Base through the x402 protocol, requiring no platform account or payment processor.
    MIT
Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.