Zebu Data - Amazon & eBay Product Data
Server Details
Amazon and eBay search results, product details, prices, variants and customer reviews.
- Status
- Healthy
- Uptime
- 48.4% over 22 days
- OAuth
- Works in Glama
- Last Tested
- Transport
- Streamable HTTP · MCP 2025-11-25
- URL
- Repository
- zebudata/claude-plugins
- GitHub Stars
- 0
TDQS
Scored across 4 tools
Each tool targets a distinct resource/action: abort a run, inspect a run, read dataset items, read a key-value record. The two 'actor-run' tools differ clearly (abort vs. get), and the two read tools operate on different storage types (dataset vs. key-value store). No plausible confusion between any pair.
All four names follow a consistent kebab-case verb-resource pattern (abort-actor-run, get-actor-run, get-dataset-items, get-key-value-store-record). The convention is uniform and predictable, with 'get-*' grouping the retrieval operations.
Four tools is thin for a server framed around Amazon & eBay product data scraping, since all four are generic Apify storage primitives. Each tool arguably earns its place, but the surface feels under-built for the advertised purpose.
There is no tool to start/run an Actor, list Actors, or list datasets/stores, so an agent cannot initiate the data-extraction workflow the server implies. Only abort plus read operations are exposed, leaving a significant lifecycle gap.
Available Tools
5 toolsabort-actor-runAbort Actor runADestructiveIdempotentInspect
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
| Name | Required | Description | Default |
|---|---|---|---|
| runId | Yes | The ID of the Actor run to abort. | |
| gracefully | No | If true, the Actor run will abort gracefully with a 30-second timeout. |
Output Schema
| Name | Required | Description |
|---|---|---|
| tip | No | Advisory guidance RAG Web Browser wrote to its key-value store under the reserved "TIP" key |
| runId | Yes | Actor run ID |
| stats | No | Run statistics |
| status | Yes | Run status: READY | RUNNING | TIMING-OUT | TIMED-OUT | ABORTING | ABORTED | SUCCEEDED | FAILED |
| actorId | Yes | Stable Apify Actor ID from the run record |
| summary | Yes | Past-tense summary of the run state |
| exitCode | No | Actor process exit code; populated for terminal states (especially FAILED) |
| nextStep | Yes | One primary follow-up action with identifiers interpolated |
| storages | Yes | Dataset and key-value store metadata, keyed by alias. "default" is always the primary entry. |
| actorName | No | "username/actor-name" |
| startedAt | No | ISO timestamp when the run started |
| finishedAt | No | ISO timestamp when the run finished (terminal states only) |
| statusMessage | No | Pass-through from Apify run.statusMessage |
| apifyConsoleUrl | No | Personalized Apify Console link to the run; present only for Console sessions |
TDQS
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.
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.
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.
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.
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.
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.
delicious_zebu--amazon-product-details-scraperdelicious_zebu/amazon-product-details-scraperCDestructiveInspect
This tool calls the Actor "delicious_zebu/amazon-product-details-scraper" and retrieves its output results. Actor description: Turn ASINs or Amazon product URLs into full product records: price, list price, coupons, Best Sellers Rank, variants, stock, delivery date, sellers and offers, images, specs and review summaries. Choose the Amazon site, currency and delivery ZIP code.
| Name | Required | Description | Default |
|---|---|---|---|
| Params | Yes | **REQUIRED** Amazon product ASINs or product detail page URLs - you can mix both in the same run. - **ASIN**, e.g. `B00091S3K4` - scraped from the country site you pick in **Country website** below. - **Product URL**, e.g. `https://www.amazon.de/dp/B00091S3K4` - the domain in the URL wins, so this one is scraped from Amazon Germany no matter what **Country website** is set to. Duplicates are scraped (and charged) only once. Example values: ["B00091S3K4","https://www.amazon.com/dp/B077Z99YGY"] | |
| website | No | Which Amazon country site bare ASINs are scraped from. **Ignored for inputs that are full URLs** - those always use their own domain, so you can mix marketplaces in one run. The same ASIN can be a different product on a different country site, so pick the one your ASINs came from. Example values: "amazon.com" | amazon.com |
| zipCode | No | Optional postal code for a precise 'Deliver to' location, in the selected site's own format (e.g. 10010 for amazon.com, 160-0022 for amazon.co.jp). A code Amazon rejects falls back to the site's default location (noted in the run log). On amazon.de and amazon.co.uk the location follows a local IP instead, so zip codes can't be applied there. | |
| currency | No | Site default = the site's own currency. Amazon converts prices where it supports the chosen currency; otherwise they stay in the site's currency. On amazon.com, conversion only applies when Deliver to is outside the US. Example values: "default" | default |
| language | No | Page language. `default` keeps each country site's own language. A URL that already carries a language (e.g. `/-/en/`) keeps that language. Example values: "default" | default |
| waitSecs | No | Max 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. | |
| deliverTo | No | Delivery country for Amazon.com, same as the 'Deliver to' location in the top-left of Amazon pages (full country list from Amazon's own 'ship outside the US' menu). It affects which products are shown, prices and availability. Other country websites always deliver to their own country. For a precise location, set Zip Code below. Example values: "US" | US |
Output Schema
| Name | Required | Description |
|---|---|---|
| tip | No | Advisory guidance RAG Web Browser wrote to its key-value store under the reserved "TIP" key |
| runId | Yes | Actor run ID |
| stats | No | Run statistics |
| status | Yes | Run status: READY | RUNNING | TIMING-OUT | TIMED-OUT | ABORTING | ABORTED | SUCCEEDED | FAILED |
| actorId | Yes | Stable Apify Actor ID from the run record |
| summary | Yes | Past-tense summary of the run state |
| exitCode | No | Actor process exit code; populated for terminal states (especially FAILED) |
| nextStep | Yes | One primary follow-up action with identifiers interpolated |
| storages | Yes | Dataset and key-value store metadata, keyed by alias. "default" is always the primary entry. |
| actorName | No | "username/actor-name" |
| startedAt | No | ISO timestamp when the run started |
| finishedAt | No | ISO timestamp when the run finished (terminal states only) |
| statusMessage | No | Pass-through from Apify run.statusMessage |
| apifyConsoleUrl | No | Personalized Apify Console link to the run; present only for Console sessions |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare destructiveHint=true, openWorldHint=true and readOnlyHint=false, so the safety profile is carried structurally. The description adds nothing about the behaviors that matter for this wrapper: that it launches an actor run, that duplicate ASINs are charged once, credit consumption, or the async/polling lifecycle. For a run-invoking tool, this is a meaningful omission.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with the value proposition front-loaded in the actor description. The first sentence is largely wrapper boilerplate that could be trimmed, but overall it is compact and readable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists, so return values needn't be explained, and the schema documents all seven parameters thoroughly. What is missing is the run lifecycle and cost context implied by waitSecs ('follow nextStep to poll via get-actor-run') — an agent reading only the description would not know this call may return before the data is ready.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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 gestures at three of the seven parameters (website, currency, zipCode), but the schema already documents each in far greater depth, including the ASIN-vs-URL precedence rule. No additional meaning is contributed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The second sentence states a specific verb and resource: turning ASINs/Amazon product URLs into full product records, with a concrete enumeration of fields returned (price, BSR, variants, offers, etc.). This clearly separates it from the infrastructure siblings (abort-actor-run, get-actor-run, get-dataset-items). The leading wrapper sentence ('calls the Actor ... and retrieves its output results') is boilerplate but doesn't obscure the purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no statement of when to use this tool versus the siblings, no prerequisite (e.g. that a run may return before completion and must be polled via get-actor-run), and no exclusion of adjacent scraping cases. 'Choose the Amazon site, currency and delivery ZIP code' is parameter configuration guidance, not usage guidance.
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 runARead-onlyIdempotentInspect
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
| Name | Required | Description | Default |
|---|---|---|---|
| runId | Yes | The ID of the Actor run. | |
| waitSecs | No | Maximum 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
| Name | Required | Description |
|---|---|---|
| tip | No | Advisory guidance RAG Web Browser wrote to its key-value store under the reserved "TIP" key |
| runId | Yes | Actor run ID |
| stats | No | Run statistics |
| status | Yes | Run status: READY | RUNNING | TIMING-OUT | TIMED-OUT | ABORTING | ABORTED | SUCCEEDED | FAILED |
| actorId | Yes | Stable Apify Actor ID from the run record |
| summary | Yes | Past-tense summary of the run state |
| exitCode | No | Actor process exit code; populated for terminal states (especially FAILED) |
| nextStep | Yes | One primary follow-up action with identifiers interpolated |
| storages | Yes | Dataset and key-value store metadata, keyed by alias. "default" is always the primary entry. |
| actorName | No | "username/actor-name" |
| startedAt | No | ISO timestamp when the run started |
| finishedAt | No | ISO timestamp when the run finished (terminal states only) |
| statusMessage | No | Pass-through from Apify run.statusMessage |
| apifyConsoleUrl | No | Personalized Apify Console link to the run; present only for Console sessions |
TDQS
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.
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.
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.
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.
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.
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 itemsARead-onlyIdempotentInspect
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
| Name | Required | Description | Default |
|---|---|---|---|
| desc | No | If true, results are returned in reverse order (newest to oldest). | |
| omit | No | Comma-separated list of fields to exclude from results. | |
| clean | No | If true, returns only non-empty items and skips hidden fields (starting with #). Shortcut for skipHidden=true and skipEmpty=true. | |
| limit | No | Maximum number of items to return. Default is 20. | |
| fields | No | Comma-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. | |
| offset | No | Number of items to skip at the start. Default is 0. | |
| flatten | No | Comma-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. | |
| datasetId | Yes | Dataset ID or username~dataset-name. |
Output Schema
| Name | Required | Description |
|---|---|---|
| items | Yes | Dataset items |
| limit | Yes | Limit used for pagination |
| offset | Yes | Offset used for pagination |
| summary | Yes | Summary of the result |
| nextStep | Yes | One follow-up action with tool name |
| datasetId | Yes | Dataset ID |
| itemCount | Yes | Number of items returned |
| totalItemCount | Yes | Total items in dataset |
| apifyConsoleUrl | No | Personalized Apify Console link to the dataset; present only for Console sessions |
TDQS
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.
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.
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.
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.
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.
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 recordARead-onlyIdempotentInspect
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
| Name | Required | Description | Default |
|---|---|---|---|
| recordKey | Yes | Key of the record to retrieve. | |
| keyValueStoreId | Yes | Key-value store ID or username~store-name. |
Output Schema
| Name | Required | Description |
|---|---|---|
| key | Yes | Record key |
| value | Yes | The stored value (JSON, text, or binary) |
| summary | Yes | Summary of the result |
| contentType | No | MIME type of the stored value |
| keyValueStoreId | Yes | Key-value store ID |
TDQS
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.
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.
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.
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.
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.
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.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
5 tool updates
- Added
abort-actor-run - Added
delicious_zebu--amazon-product-details-scraper - Added
get-actor-run - Added
get-dataset-items - Added
get-key-value-store-record
5 tool updates
- Removed
abort-actor-run - Removed
delicious_zebu--amazon-product-details-scraper - Removed
get-actor-run - Removed
get-dataset-items - Removed
get-key-value-store-record
5 tool updates
- Added
abort-actor-run - Added
delicious_zebu--amazon-product-details-scraper - Added
get-actor-run - Added
get-dataset-items - Added
get-key-value-store-record
5 tool updates
- Removed
abort-actor-run - Removed
delicious_zebu--amazon-product-details-scraper - Removed
get-actor-run - Removed
get-dataset-items - Removed
get-key-value-store-record
5 tool updates
- Added
abort-actor-run - Added
delicious_zebu--amazon-product-details-scraper - Added
get-actor-run - Added
get-dataset-items - Added
get-key-value-store-record
5 tool updates
- Removed
abort-actor-run - Removed
delicious_zebu--amazon-product-details-scraper - Removed
get-actor-run - Removed
get-dataset-items - Removed
get-key-value-store-record
1 tool update
- Removed
delicious_zebu--ebay-product-details-scraper
6 tool updates
- Added
abort-actor-run - Added
delicious_zebu--amazon-product-details-scraper - Added
delicious_zebu--ebay-product-details-scraper - Added
get-actor-run - Added
get-dataset-items - Added
get-key-value-store-record
5 tool updates
- Removed
abort-actor-run - Removed
delicious_zebu--amazon-product-details-scraper - Removed
get-actor-run - Removed
get-dataset-items - Removed
get-key-value-store-record
5 tool updates
- Added
abort-actor-run - Added
delicious_zebu--amazon-product-details-scraper - Added
get-actor-run - Added
get-dataset-items - Added
get-key-value-store-record
5 tool updates
- Removed
abort-actor-run - Removed
delicious_zebu--amazon-product-details-scraper - Removed
get-actor-run - Removed
get-dataset-items - Removed
get-key-value-store-record
5 tool updates
- Added
abort-actor-run - Added
delicious_zebu--amazon-product-details-scraper - Added
get-actor-run - Added
get-dataset-items - Added
get-key-value-store-record
6 tool updates
- Removed
abort-actor-run - Removed
delicious_zebu--amazon-reviews-scraper-with-advanced-filters - Removed
delicious_zebu--ebay-product-listing-scraper - Removed
get-actor-run - Removed
get-dataset-items - Removed
get-key-value-store-record
6 tool updates
- Added
abort-actor-run - Added
delicious_zebu--amazon-reviews-scraper-with-advanced-filters - Added
delicious_zebu--ebay-product-listing-scraper - Added
get-actor-run - Added
get-dataset-items - Added
get-key-value-store-record
5 tool updates
- Removed
abort-actor-run - Removed
delicious_zebu--amazon-reviews-scraper-with-advanced-filters - Removed
get-actor-run - Removed
get-dataset-items - Removed
get-key-value-store-record
2 tool updates
- Added
delicious_zebu--amazon-reviews-scraper-with-advanced-filters - Removed
delicious_zebu--ebay-product-details-scraper
5 tool updates
- Added
abort-actor-run - Added
delicious_zebu--ebay-product-details-scraper - Added
get-actor-run - Added
get-dataset-items - Added
get-key-value-store-record
5 tool updates
- Removed
abort-actor-run - Removed
delicious_zebu--ebay-product-listing-scraper - Removed
get-actor-run - Removed
get-dataset-items - Removed
get-key-value-store-record
5 tool updates
- Added
abort-actor-run - Added
delicious_zebu--ebay-product-listing-scraper - Added
get-actor-run - Added
get-dataset-items - Added
get-key-value-store-record
5 tool updates
- Removed
abort-actor-run - Removed
delicious_zebu--ebay-product-listing-scraper - Removed
get-actor-run - Removed
get-dataset-items - Removed
get-key-value-store-record
Related MCP Connectors
Products, prices and sellers from Amazon, Taobao/Tmall, AliExpress, TikTok Shop and Idealo (EU).
Amazon marketplace data for products, offers, reviews, sellers, search, categories, and deals.
Search AliExpress and eBay in any language: real listings with price, rating, delivery and links.
Product search across online shops worldwide, plus every seller's price with a direct link.
Related MCP Servers
- AlicenseNot gradedqualityDmaintenanceAnalyzes Amazon products with comprehensive insights including pricing, features, specifications, delivery options, and customer reviews, displayed through an interactive React widget.MIT
- FlicenseNot gradedqualityBmaintenanceEnables AI agents to search and compare live UK product prices from marketplaces like eBay and Amazon, returning normalised JSON with direct buy links.-

idealo MCP Serverofficial
AlicenseNot gradedqualityFmaintenanceEnables product search, price comparison, and price history analysis across 6 European marketplaces (DE, AT, GB, FR, IT, ES).19MIT- AlicenseAqualityAmaintenanceLive Amazon marketplace data for AI agents: product details, prices, reviews, keyword search, best-sellers, deals, offers and stock, and seller profiles across 20 marketplaces.12MIT
Glama MCP Gateway
Add one secure layer between your agents and this server.