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BACH-AI-Tools

Real Time Amazon Data MCP Server

deals

Retrieve Amazon deals across all types including Today's Deals, Top Deals, Best Deals, and Lightning Deals. Filter by brand, category, price, discount, rating, and more.

Instructions

Get Amazon Deals (Today's Deals / Top Deals, Best Deals, and Lightning Deals) with support for all deal types, filters, and options available on Amazon.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
brandsNoReturn deals with products by specific brands. Multiple brands can be specified separated by comma (,). In addition, brand names can be found under the Brand filter on the filter/refinements panel on https://www.amazon.com/deals (when applicable). Examples: AQUA CREST Daixers,Antarctic Star
fieldsNoA comma separated list of deal fields to include in the response (field projection). By default all fields are returned. Example: deal_type,deal_title,deal_ends_at,savings_amount
offsetNoNumber of results to skip / index to start from (for pagination).0
countryNoSets the Amazon domain, marketplace country, language and currency. Default: US Allowed values: US, AU, BR, CA, CN, FR, DE, IN, IT, MX, NL, SG, ES, TR, AE, GB, JP, SA, PL, SE, BE, EG
languageNoThe language of the results. In case not specified, results will be returned in the default domain language. Supported languages per country: US: en_US, es_US AU: en_AU BR: pt_BR CA: en_CA, fr_CA FR: fr_FR, en_GB DE: de_DE, en_GB, cs_CZ, nl_NL, pl_PL, tr_TR, da_DK IN: en_IN, hi_IN, ta_IN, te_IN, kn_IN, ml_IN, bn_IN, mr_IN IT: it_IT, en_GB MX: es_MX NL: nl_NL, en_GB SG: en_SG ES: es_ES, pt_PT, en_GB TR: tr_TR AE: en_AE, ar_AE GB: en_GB JP: ja_JP, en_US, zh_CN SA: ar_AE, en_AE PL: pl_PL SE: sv_SE,
categoriesNoReturn deals with products in specific categories / departments. Multiple categories can be specified as a comma (,) separated list. Numeric category id's can be found in the URL after selecting a specific category on https://www.amazon.com/deals. Examples: 502394 2619525011,2617941011
price_rangeNoReturn deals with price within a specific price range. 1 is lowest price range shown on Amazon (e.g. Under $25) while 5 is the highest price range (e.g. $200 & Above). Default: ALL Allowed values: ALL, 1, 2, 3, 4, 5
discount_rangeNoReturn deals with discount within a specific discount range. 1 is lowest discount range shown on Amazon (e.g. 10% off or more) while 5 is the highest discount range (e.g. 70% off or more). Default: ALL Allowed values: ALL, 1, 2, 3, 4, 5
lightning_dealsNoExample value:
prime_exclusiveNoExample value:
prime_early_accessNoExample value:
min_product_star_ratingNoReturn deals with products star rating greater than a specific value Default: ALL Allowed values: ALL, 1, 2, 3, 4
Behavior2/5

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

No annotations are provided, so the description carries the full burden. The description says deals are fetched but doesn't disclose whether results reflect live availability, whether deals expire/change, pagination behavior, rate limits, or authentication requirements. For a shopping/price tool, freshness and real-time nature of data would be important behavioral context not disclosed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is one moderately-sized sentence and is reasonably front-loaded with the core purpose. However, it's somewhat generic and could be tightened. It doesn't enumerate the full filter capabilities despite claiming 'all filters and options' support.

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?

With 12 parameters, no annotations, no output schema, and three parameters having effectively empty descriptions, the tool is under-documented. The description claims broad capability ('all deal types, filters, and options') but this is vague and doesn't enumerate specifics. For a complex tool with this many parameters, more detail on the returned deal structure and how filters interact would be needed.

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 baseline is 3. The description adds minimal value beyond the schema since it broadly mentions 'filters and options' without detailing specific parameters. Some parameters like lightning_deals, prime_exclusive, and prime_early_access have empty descriptions ('Example value: '), and the main description doesn't clarify their semantics. The description does not compensate for these gaps.

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 states 'Get Amazon Deals' with specific deal types (Today's Deals / Top Deals, Best Deals, Lightning Deals) and mentions filters/options. It clearly identifies the subject (deals) and distinguishes from sibling tools like deal_products and product_search. However, it could be more specific about what data is returned per deal (e.g., savings, prices).

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

Usage Guidelines2/5

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

No guidance on when to use this tool vs. alternatives. With sibling deal_products, best_sellers, and product_search tools, the description doesn't explain what distinguishes deals from best_sellers or deal_products specifically. Context about when one would prefer this over deal_products or best_sellers is absent.

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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